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Sanjib Sharma

Publications and source records attributed to Sanjib Sharma.

At least 37 records · Page 2Linked to original sources

The GALAH survey: Elemental abundances in open clusters using joint effective temperature and surface gravity photometric priors

The ability to measure precise and accurate stellar effective temperatures ($T_{\rm{eff}}$) and surface gravities ($\log(g)$) is essential in determining accurate and precise abundances of chemical elements in stars. Measuring $\log(g)$ from isochrones fitted to colour-magnitude diagrams of open clusters is significantly more accurate and precise compared to spectroscopic $\log(g)$. By determining the ranges of ages, metallicity, and extinction of isochrones that fit the colour-magnitude diagram, we constructed a joint probability distribution of $T_{\rm{eff}}$ and $\log(g)$. The joint photometric probability shows the complex correlations between $T_{\rm{eff}}$ and $\log(g)$, which depend on the evolutionary stage of the star. We show that by using this photometric prior while fitting spectra, we can acquire more precise spectroscopic stellar parameters and abundances of chemical elements. This reveals higher-order abundance trends in open clusters like traces of atomic diffusion. We used photometry and astrometry provided by the \textit{Gaia} DR3 catalogue, Padova isochrones, and Galactic Archaeology with HERMES (GALAH) DR4 spectra. We analysed the spectra of 1979 stars in nine open clusters, using MCMC to fit the spectroscopic abundances of 26 elements, $T_{\rm{eff}}$, $\log(g)$, $v_{\rm{mic}}$, and $v_{\rm{broad}}$. We found that using photometric priors improves the accuracy of abundances and $\log(g)$, which enables us to view higher-order trends of abundances caused by atomic diffusion in M67 and Ruprecht 147.

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Asteroseismology with the Roman Galactic Bulge Time-Domain Survey

Asteroseismology has transformed stellar astrophysics. Red giant asteroseismology is a prime example, with oscillation periods and amplitudes that are readily detectable with time-domain space-based telescopes. These oscillations can be used to infer masses, ages and radii for large numbers of stars, providing unique constraints on stellar populations in our galaxy. The cadence, duration, and spatial resolution of the Roman galactic bulge time-domain survey (GBTDS) are well-suited for asteroseismology and will probe an important population not studied by prior missions. We identify photometric precision as a key requirement for realizing the potential of asteroseismology with Roman. A precision of 1 mmag per 15-min cadence or better for saturated stars will enable detections of the populous red clump star population in the Galactic bulge. If the survey efficiency is better than expected, we argue for repeat observations of the same fields to improve photometric precision, or covering additional fields to expand the stellar population reach if the photometric precision for saturated stars is better than 1 mmag. Asteroseismology is relatively insensitive to the timing of the observations during the mission, and the prime red clump targets can be observed in a single 70 day campaign in any given field. Complementary stellar characterization, particularly astrometry tied to the Gaia system, will also dramatically expand the diagnostic power of asteroseismology. We also highlight synergies to Roman GBTDS exoplanet science using transits and microlensing.

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RomAndromeda: The Roman Survey of the Andromeda Halo

As our nearest large neighbor, the Andromeda Galaxy provides a unique laboratory for investigating galaxy formation and the distribution and substructure properties of dark matter in a Milky Way-like galaxy. Here, we propose an initial 2-epoch ($Δt\approx 5$yr), 2-band Roman survey of the entire halo of Andromeda, covering 500 square degrees, which will detect nearly every red giant star in the halo (10$σ$ detection in F146, F062 of 26.5, 26.1AB mag respectively) and yield proper motions to $\sim$25 microarcsec/year (i.e., $\sim$90 km/s) for all stars brighter than F146 $\approx 23.6$ AB mag (i.e., reaching the red clump stars in the Andromeda halo). This survey will yield (through averaging) high-fidelity proper motions for all satellites and compact substructures in the Andromeda halo and will enable statistical searches for clusters in chemo-dynamical space. Adding a third epoch during the extended mission will improve these proper motions by $\sim t^{-1.5}$, to $\approx 11$ km/s, but this requires obtaining the first epoch in Year 1 of Roman operations. In combination with ongoing and imminent spectroscopic campaigns with ground-based telescopes, this Roman survey has the potential to yield full 3-d space motions of $>$100,000 stars in the Andromeda halo, including (by combining individual measurements) robust space motions of its entire globular cluster and most of its dwarf galaxy satellite populations. It will also identify high-velocity stars in Andromeda, providing unique information on the processes that create this population. These data offer a unique opportunity to study the immigration history, halo formation, and underlying dark matter scaffolding of a galaxy other than our own.

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CN and CO Features: Key Indicators of Red Giant Evolutionary Phase in Moderate-Resolution X-Shooter Spectra

Data-driven analysis methods can help to infer physical properties of red giant stars where "gold-standard" asteroseismic data are not available. The study of optical and infrared spectra of red giant stars with data-driven analyses has revealed that differences in oscillation frequencies and their separations are imprinted in said spectra. This makes it possible to confidently differentiate core-helium burning red clump stars (RC) from those that are still on their first ascent of the red giant branch (RGB). We extend these studies to a tenfold larger wavelength range of 0.33 to 2.5 microns with the moderate-resolution VLT/X-shooter spectrograph. Our analysis of 49 stars with asteroseismic data from the K2 mission confirms that CN, CO and CH features are indeed the primary carriers of spectroscopic information on the evolutionary stages of red giant stars. We report 215 informative features for differentiating the RC from the RGB within the range of 0.33 to 2.5 microns. This makes it possible for existing and future spectroscopic surveys to optimize their wavelength regions to deliver both a large variety of elemental abundances and reliable age estimates of luminous red giant stars.

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Chemical Evolution with Radial Mixing Redux: Extending beyond the Solar Neighborhood

We present a multi-zone galactic chemical evolution (GCE) model for the Milky Way that takes the most recently updated yields of major nucleosynthesis channels into account. It incorporates physical processes commonly found in previous GCE models like supernova and star formation feedback, the radial flow of gas in the disk, and the infall of fresh gas, along with stellar scattering processes like radial migration. We individually analyse the effect of different physical processes present in our model on the observed properties of the Galaxy. The radial flow of gas in the disk plays an important role in establishing the radial gradient for \feh{} in the low-\alphafe{} sequence. Our model with one episode of smooth gas infall and constant star formation efficiency is capable of reproducing the observed \fehalpha{} distribution of stars at different ($R$, $|z|$) positions in the Milky Way. Our results point to the rapid evolution of \alphafe{} after the onset of Type Ia supernovae and a high star formation rate during the formation of the high-\alphafe{} sequence as the origin of dual peaks in \alphafe{}. A secondary infall is unnecessary to reproduce the \alphafe{}-gap and chemical spread in the disk in our model. We additionally compare the median age for various mono-abundance populations and the age-metallicity relation at different ($R$, $|z|$) positions from our fiducial model to observations. We discuss our results in relation to other related work in detail.

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Nepal Himalaya Offers Considerable Potential for Pumped Storage Hydropower

There is a pressing need for a transition from fossil fuel to renewable energy to meet the increasing energy demands and reduce greenhouse gas (GHG) emissions. The Himalayas possess substantial renewable energy potential that can be harnessed through hydropower projects due to its peculiar topographic characteristics and abundant water resources. However, the current exploitation rate is low owing to the predominance of run-of-river hydropower systems to support the power system. The utility-scale storage facility is crucial in the load scenario of an integrated power system to manage diurnal variation, peak demand, and penetration of intermittent energy sources. In this study, we first identify the potential of pumped storage hydropower across Nepal (a central Himalayan country) under multiple configurations by pairing lakes, hydropower projects, rivers, and available flat terrains. We then identify technically feasible pairs from those of potential locations. Infrastructural, environmental, operational, and other technical constraints govern the choice of feasible locations. We find the flat land-to-river configuration most promising than other configurations. Our results provide insight into the potential of pumped storage hydropower and are of practical importance in planning sustainable power systems in the Himalayas and beyond.

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Measuring the Streaming motion in the Milky Way disc with Gaia EDR3 +

We map the 3D kinematics of the Galactic disc out to 3.5 kpc from the Sun, and within 0.75 kpc from the midplane of the Galaxy. To this end, we combine high quality astrometry from \gedrthree{}, with heliocentric line-of-sight velocities from \gdrtwo{}, and spectroscopic surveys including \apogee{}, \galah{}, and \lamost{}. We construct an axisymmetric model for the mean velocity field, and subtract this on a star-by-star basis to obtain the residual velocity field in the Galactocentric components (\vphi{}, \vR, \vz), and \vlos{}. The velocity residuals are quantified using the power spectrum, and we find that the peak power ($A/$[\rm \kms{}]) in the midplane ($|z|<0.25$ kpc) is ($A_ϕ,A_{\rm R},A_{\rm Z},A_{\rm los}$)=($4.2,8.5,2.6,4.6$), at $0.25 < |z|/[{\rm kpc}] < 0.5$, is ($A_ϕ,A_{\rm R},A_{\rm Z},A_{\rm los}$)=($4.0,7.9,3.6,5.3$), and at $0.5 < |z|/[{\rm kpc}] < 0.75$, is ($A_ϕ,A_{\rm R},A_{\rm Z},A_{\rm los}$)=($1.9,6.9,5.2,6.4$). Our results provide a sophisticated measurement of the streaming motion in the disc and in the individual components. We find that streaming is most significant in \vR, and at all heights ($|Z|$) probed, but is also non-negligible in other components. Additionally, we find that patterns in velocity field overlap spatially with models for Spiral arms in the Galaxy. Our simulations show that phase-mixing of disrupting spiral arms can generate such residuals in the velocity field, where the radial component is dominant, just as in real data. We also find that with time evolution both the amplitude and physical scale of the residual motion decrease.

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Machine Learning for Postprocessing Ensemble Streamflow Forecasts

Skillful streamflow forecasts can inform decisions in various areas of water policy and management. We integrate numerical weather prediction ensembles, distributed hydrological model and machine learning to generate ensemble streamflow forecasts at medium-range lead times (1 - 7 days). We demonstrate a case study for machine learning applications in postprocessing ensemble streamflow forecasts in the Upper Susquehanna River basin in the eastern United States. Our results show that the machine learning postprocessor can improve streamflow forecasts relative to low complexity forecasts (e.g., climatological and temporal persistence) as well as standalone hydrometeorological modeling and neural network. The relative gain in forecast skill from postprocessor is generally higher at medium-range timescales compared to shorter lead times; high flows compared to low-moderate flows, and warm-season compared to cool ones. Overall, our results highlight the benefits of machine learning in many aspects for improving both the skill and reliability of streamflow forecasts.

cs.LG↗

The Galactic Underworld: The spatial distribution of compact remnants

We chart the expected Galactic distribution of neutron stars and black holes. These compact remnants of dead stars -- the Galactic underworld -- are found to exhibit a fundamentally different distribution and structure to the visible Galaxy. Compared to the visible Galaxy, concentration into a thin flattened disk structure is much less evident with the scale height more than tripling to 1260 +- 30 pc. This difference arises from two primary causes. Firstly, the distribution is in part inherited from the integration over the evolving structure of the Galaxy itself (and hence the changing distribution of the parent stars). Secondly, an even larger effect arises from the natal kick received by the remnant at the event of its supernova birth. Due to this kick we find 30% of remnants have sufficient kinetic energy to entirely escape the Galactic potential (40% of neutron stars and 2% of black holes) leading to a Galactic mass loss integrated to the present day of ~ 0.4% of the stellar mass of the Galaxy. The black hole -- neutron star fraction increases near the Galactic centre: a consequence of smaller kick velocities in the former (the assumption made is that kick velocity is inversely proportional to mass). Our simulated remnant distribution yields probable distances of 19 pc and 21 pc to the nearest neutron star and black hole respectively, while our nearest probable magnetar lies at 4.2 kpc. Although the underworld only contains of order ~ 1% of the Galaxy's mass, observational signatures and physical traces of its population, such as microlensing, will become increasingly present in data ranging from gravitational wave detectors to high precision surveys from space missions such as Gaia.

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The GALAH Survey: A New Sample of Extremely Metal-Poor Stars Using A Machine Learning Classification Algorithm

Extremely Metal-Poor (EMP) stars provide a valuable probe of early chemical enrichment in the Milky Way. Here we leverage a large sample of $\sim600,000$ high-resolution stellar spectra from the GALAH survey plus a machine learning algorithm to find 54 candidates with estimated [Fe/H]~$\leq$~-3.0, 6 of which have [Fe/H]~$\leq$~-3.5. Our sample includes $\sim 20 \%$ main sequence EMP candidates, unusually high for \emp surveys. We find the magnitude-limited metallicity distribution function of our sample is consistent with previous work that used more complex selection criteria. The method we present has significant potential for application to the next generation of massive stellar spectroscopic surveys, which will expand the available spectroscopic data well into the millions of stars.

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Streams on FIRE: Populations of Detectable Stellar Streams in the Milky Way and FIRE

We present the first detailed study comparing the populations of stellar streams in cosmological simulations to observed Milky Way dwarf galaxy streams. In particular, we compare streams identified around Milky Way analogs in the FIRE-2 simulations to stellar streams observed by the Southern Stellar Stream Spectroscopic Survey (S5). For an accurate comparison between the stream populations, we produce mock Dark Energy Survey (DES) observations of the FIRE streams and estimate the detectability of their tidal tails and progenitors. The number and stellar mass distributions of detectable stellar streams is consistent between observations and simulations. However, there are discrepancies in the distributions of pericenters and apocenters, with the detectable FIRE streams, on average, forming at larger pericenters (out to > 110 kpc) and surviving only at larger apocenters (> 40 kpc) than those observed in the Milky Way. We find that the population of high-stellar mass dwarf galaxy streams in the Milky Way is incomplete. Interestingly, a large fraction of the FIRE streams would only be detected as satellites in DES-like observations, since their tidal tails are too low-surface brightness to be detectable. We thus predict a population of yet-undetected tidal tails around Milky Way satellites, as well as a population of fully undetected low surface brightness stellar streams, and estimate their detectability with the Rubin Observatory. Finally, we discuss the causes and implications of the discrepancies between the stream populations in FIRE and the Milky Way, and explore future avenues for tests of satellite disruption in cosmological simulations.

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Flood hazard model calibration using multiresolution model output

Riverine floods pose a considerable risk to many communities. Improving flood hazard projections has the potential to inform the design and implementation of flood risk management strategies. Current flood hazard projections are uncertain, especially due to uncertain model parameters. Calibration methods use observations to quantify model parameter uncertainty. With limited computational resources, researchers typically calibrate models using either relatively few expensive model runs at high spatial resolutions or many cheaper runs at lower spatial resolutions. This leads to an open question: Is it possible to effectively combine information from the high and low resolution model runs? We propose a Bayesian emulation-calibration approach that assimilates model outputs and observations at multiple resolutions. As a case study for a riverine community in Pennsylvania, we demonstrate our approach using the LISFLOOD-FP flood hazard model. The multiresolution approach results in improved parameter inference over the single resolution approach in multiple scenarios. Results vary based on the parameter values and the number of available models runs. Our method is general and can be used to calibrate other high dimensional computer models to improve projections.

stat.ME↗

Can radial motions in the stellar halo constrain the rate of change of mass in the Galaxy?

A change in the mass of the Galaxy with time will leave its imprint on the motions of the stars, with stars having radially outward (mass loss) or inward (mass accretion) bulk motions. Here we test the feasibility of using the mean radial motion of stars in the stellar halo to constrain the rate of change of mass in the Galaxy, for example, due to decay of dark matter into invisible dark sector particles or more conservatively from the settling of baryons. In the current $Λ$CDM paradigm of structure formation, the stellar halo is formed by accretion of satellites onto the host galaxy. Over time, as the satellites disrupt and phase mix, the mean radial motion $\langle V_{R} \rangle$ of the stellar halo is eventually expected to be close to zero. But most halos have substructures due to incomplete mixing of specific accretion events and this can lead to nonzero $\langle V_{R} \rangle$ in them. Using simulations, we measure the mean radial motion, $\langle V_{R} \rangle$, of stars in 13 $Λ$CDM stellar halos lying in a spherical shell of radius 30 kpc. We find that for most halos, the shell motion is quite small, with 75\% of halos having $\langle V_{R}\rangle \lesssim 1.2 \ {\rm km}s^{-1}$. When substructures are removed by using a clustering algorithm, $\langle V_{R}\rangle$ is reduced even further, with 75\% of halos having $\langle V_{R}\rangle \lesssim 0.6 \ {\rm km}s^{-1}$. A value of $\langle V_{R}\rangle \approx 0.6 \ {\rm km}s^{-1}$ can be attained corresponding to a galactic mass loss rate of 2\% per Gyr. We show that this can place constraints on dark matter decay parameters such as the decay lifetime and the kick velocity that is imparted to the daughter particle. The advent of all-sky stellar surveys involving millions to billions of stars is encouraging for detecting signatures of dark matter decay.

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Reliable stellar abundances of individual stars with the MUSE integral-field spectrograph

We present a novel approach to deriving stellar labels for stars observed in MUSE fields making use of data-driven machine learning methods. Taking advantage of the comparable spectral properties (resolution, wavelength coverage) of the LAMOST and MUSE instruments, we adopt the Data-Driven Payne (DD-Payne) model used on LAMOST observations and apply it to stars observed in MUSE fields. Remarkably, in spite of instrumental differences, according to the cross-validation of 27 LAMOST-MUSE common stars, we are able to determine stellar labels with precision better than 75K in $T_{\rm eff}$, 0.15 dex in $\log g$, and 0.1 dex in abundances of [Fe/H], [Mg/Fe], [Si/Fe], [Ti/Fe], [C/Fe], [Ni/Fe] and [Cr/Fe] for current MUSE observations over a parameter range of 3800<$T_{\rm eff}$<7000 K, -1.5<[Fe/H]<0.5 dex. To date, MUSE has been used to target 13,000 fields across the southern sky since it was first commissioned six years ago and it is unique in its ability to study dense star fields such as globular clusters or the Milky Way bulge. Our method will enable the automated determination of stellar parameters for all stars in these fields. Additionally, it opens the door for applications to data collected by other spectrographs having resolution similar to LAMOST. With the upcoming BlueMUSE and MAVIS, we will gain access to a whole new range of chemical abundances with higher precision, especially critical s-process elements such as [Y/Fe] and [Ba/Fe] that provide key age diagnostics for stellar targets.

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Discovery of post-mass-transfer helium-burning red giants using asteroseismology

A star expands to become a red giant when it has fused all the hydrogen in its core into helium. If the star is in a binary system, its envelope can overflow onto its companion or be ejected into space, leaving a hot core and potentially forming a subdwarf-B star. However, most red giants that have partially transferred envelopes in this way remain cool on the surface and are almost indistinguishable from those that have not. Among $\sim$7000 helium-burning red giants observed by NASA's Kepler mission, we use asteroseismology to identify two classes of stars that must have undergone dramatic mass loss, presumably due to stripping in binary interactions. The first class comprises about 7 underluminous stars with smaller helium-burning cores than their single-star counterparts. Theoretical models show that these small cores imply the stars had much larger masses when ascending the red giant branch. The second class consists of 32 red giants with masses down to 0.5 M$_\odot$, whose implied ages would exceed the age of the universe had no mass loss occurred. The numbers are consistent with binary statistics, and our results open up new possibilities to study the evolution of post-mass-transfer binary systems.

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Combined APOGEE-GALAH stellar catalogues using the Cannon

APOGEE and GALAH are two high resolution multi-object spectroscopic surveys that provide fundamental stellar parameters and multiple elemental abundance estimates for about half a million stars in the Milky Way. Both surveys observe in different wavelength regimes and use different data reduction pipelines leading to significant offsets and trends in stellar parameters and abundances for the common stars observed in both surveys. Such systematic differences/offsets in stellar parameters and abundances make it difficult to effectively utilise them to investigate Galactic abundance trends in spite of the unique advantage provided by their complementary sky coverage and different Milky Way components they observe. Hence, we use the \textit{Cannon} data-driven method selecting a training set of 4418 common stars observed by both surveys. This enables the construction of two catalogues, one with the APOGEE scaled and the other with the GALAH scaled stellar parameters. Using repeat observations in APOGEE and GALAH, we find high precision in metallicity (~ 0.02-0.4 dex) and alpha abundances (~ 0.02-0.03 dex) for spectra with good signal-to-noise ratio (SNR > 80 for APOGEE, SNR > 40 for GALAH). We use open and globular clusters to validate our parameter estimates and find small scatter in metallicity (0.06 dex) and alpha abundances (0.03 dex) in APOGEE scaled case. The final catalogues have been cross matched with the Gaia EDR3 catalogue to enable their use to carry out detailed chemo-dynamic studies of the Milky Way from perspectives of APOGEE and GALAH.

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The K2 Galactic Archaeology Program Data Release 3: Age-abundance patterns in C1-C8 and C10-C18

We present the third and final data release of the K2 Galactic Archaeology Program (K2 GAP) for Campaigns C1-C8 and C10-C18. We provide asteroseismic radius and mass coefficients, $κ_R$ and $κ_M$, for $\sim 19,000$ red giant stars, which translate directly to radius and mass given a temperature. As such, K2 GAP DR3 represents the largest asteroseismic sample in the literature to date. K2 GAP DR3 stellar parameters are calibrated to be on an absolute parallactic scale based on Gaia DR2, with red giant branch and red clump evolutionary state classifications provided via a machine-learning approach. Combining these stellar parameters with GALAH DR3 spectroscopy, we determine asteroseismic ages with precisions of $\sim 20-30\%$ and compare age-abundance relations to Galactic chemical evolution models among both low- and high-$α$ populations for $α$, light, iron-peak, and neutron-capture elements. We confirm recent indications in the literature of both increased Ba production at late Galactic times, as well as significant contribution to r-process enrichment from prompt sources associated with, e.g., core-collapse supernovae. With an eye toward other Galactic archaeology applications, we characterize K2 GAP DR3 uncertainties and completeness using injection tests, suggesting K2 GAP DR3 is largely unbiased in mass/age and with uncertainties of $2.9\%\,(\rm{stat.})\,\pm0.1\%\,(\rm{syst.})$ & $6.7\%\,(\rm{stat.})\,\pm0.3\%\,(\rm{syst.})$ in $κ_R$ & $κ_M$ for red giant branch stars and $4.7\%\,(\rm{stat.})\,\pm0.3\%\,(\rm{syst.})$ & $11\%\,(\rm{stat.})\,\pm0.9\%\,(\rm{syst.})$ for red clump stars. We also identify percent-level asteroseismic systematics, which are likely related to the time baseline of the underlying data, and which therefore should be considered in TESS asteroseismic analysis.

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The Global Dynamical Atlas of the Milky Way mergers: Constraints from Gaia EDR3 based orbits of globular clusters, stellar streams and satellite galaxies

The Milky Way halo was predominantly formed by the merging of numerous progenitor galaxies. However, our knowledge of this process is still incomplete, especially in regard to the total number of mergers, their global dynamical properties and their contribution to the stellar population of the Galactic halo. Here, we uncover the Milky Way mergers by detecting groupings of globular clusters, stellar streams and satellite galaxies in action ($\mathbf{J}$) space. While actions fully characterize the orbits, we additionally use the redundant information on their energy ($\textit{E}$) to enhance the contrast between groupings. For this endeavour, we use $\textit{Gaia}$ EDR3 based measurements of $170$ globular clusters, $41$ streams and $46$ satellites to derive their $\mathbf{J}$ and $\textit{E}$. To detect groups, we use the $\texttt{ENLINK}$ software, coupled with a statistical procedure that accounts for the observed phase-space uncertainties of these objects. We detect a total of $N=6$ groups, including the previously known mergers $\textit{Sagittarius}$, $\textit{Cetus}$, $\textit{Gaia-Sausage/Enceladus}$, $\textit{LMS-1/Wukong}$, $\textit{Arjuna/Sequoia/I'itoi}$ and one new merger that we call $\textit{Pontus}$. All of these mergers, together, comprise $62$ objects ($\approx 25\%$ of our sample). We discuss their members, orbital properties and metallicity distributions. We find that the three most metal-poor streams of our Galaxy -- "C-19" ([Fe/H]$=-3.4$ dex), "Sylgr" ([Fe/H]$=-2.9$ dex) and "Phoenix" ([Fe/H]$=-2.7$ dex) -- are associated with $\textit{LMS-1/Wukong}$; showing it to be the most metal-poor merger. The global dynamical atlas of Milky Way mergers that we present here provides a present-day reference for galaxy formation models.

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