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The Galactic Bulge exploration V.: The secular spherical and X-shaped Milky Way bulge

T0 review · 2 major / 5 minor · reviewed 2026-08-15 · deepseek-v4-flash

Pith's one-line read The paper argues that the Milky Way's spheroidal, slowly rotating bulge component—long read as a merger-built classical bulge—can instead be produced secularly by the bar's angular-momentum exchange, supported by 8,456 RR Lyrae orbits and…

desk verdict Read it for the 6D RR Lyrae data and orbit classifications; the 'secular spherical bulge' conclusion is not supported by the paper's own simulation comparison. read the letter →

arxiv 2506.19074 v2 pith:UTAZNEE7 submitted 2025-06-23 astro-ph.GA astro-ph.SR

classification astro-ph.GAastro-ph.SR
keywords GalacticbulgeRRLyraestarsstellarorbitsbar-drivensecularevolutionretrogradeMilkyWaybarN-bodysimulationsformation
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper tries to establish that the Milky Way's spheroidal, slowly rotating bulge component—usually read as the imprint of a merger-built classical bulge—can instead be produced entirely by secular bar evolution. Using full six-dimensional phase-space information for 8,456 bulge RR Lyrae stars, it classifies orbits in the bar's rotating frame and finds that the retrograde (counter-rotating) fraction rises linearly toward metal-poor stars and toward the Galactic center. Those retrograde orbits are as regular as prograde ones and together form a centrally concentrated, nearly spherical structure. An isolated N-body+SPH simulation that forms a bar without any merger reproduces the same trends, with stars oscillating between prograde and retrograde states as the bar exchanges angular momentum and slows down. The paper concludes that the spheroidal element is a real secondary component of the bulge built by the bar itself, so a massive classical bulge is not required.

What carries the argument

The load-bearing object is the sign of the azimuthal frequency in the bar's rotating frame, $\Omega^{\rm rot}_{\varphi} = \Omega^{\rm ine}_{\varphi} - \Omega_{\rm P}$, which separates bar-supporting prograde stars from retrograde stars (negative values). Around this, the paper builds a classification of orbital families (banana, brezel, fish, and x- and z-tube orbits) from frequency maps, plus a chaoticity measure, the frequency drift $\log_{10}\Delta\Omega$, showing that retrograde and prograde orbits have comparable regularity. The mechanism is completed by the isolated N-body+SPH simulation: tracking old stellar particles across snapshots shows them migrating through the vertical inner Lindblad resonance and inner Lindblad resonance, repeatedly exchanging angular momentum and flipping between prograde and retrograde states, with the retrograde fraction stabilizing within a few gigayears after bar formation.

What would settle it

Measure [α/Fe] abundances for the retrograde, centrally concentrated bulge RR Lyrae stars. If the secular scenario is right, these stars should be an old, relatively α-rich population present before bar formation; if a large fraction turn out to be young or α-poor, the claim that the spheroidal component is made by bar-driven angular-momentum exchange would be falsified.

Watch

Extended reading notes

Core claim

On the paper's own terms, the discovery is that the spheroidal component of the Galactic bulge is a genuine secondary structure whose origin is secular rather than accretional. The evidence is orbital: in the bar's rotating frame, roughly 72% of bulge RR Lyrae stars are prograde while the rest are retrograde, and the retrograde fraction grows monotonically from about 10–15% at the metal-rich end to about 30% at the metal-poor end, and toward the center reaches about 40% at Galactocentric radius near 0.5 kpc. Retrograde orbits are just as regular (low frequency drift and Lyapunov exponents) as prograde orbits, so they form a stable, nearly spherical central concentration. In the isolated HG1 simulation, only about seven percent of the retrograde particles stay retrograde over five gigayears; most oscillate across the inner Lindblad resonance, and the prograde/retrograde ratio stabilizes a few gigayears after bar formation. The paper concludes that angular-momentum exchange with the slowing bar can manufacture a classical-bulge-like spheroid from old, low-angular-momentum stars already present before the bar, making a massive merger-built classical bulge unnecessary.

Load-bearing premise

The whole secular interpretation rests on a single isolated simulation in which a bar forms without any merger; if that simulation's retrograde fraction, orbital stability, or age trends are not representative of the real Milky Way, the central claim weakens even though the observed orbit classifications remain valid.

Editorial extensions

If this is right

  • Removing retrograde stars from the metal-poor RR Lyrae sample reveals a weak rotation signal that is otherwise invisible, explaining the apparent absence of rotation in the metal-poor bulge.
  • RR Lyrae stars on banana orbits show a double-peaked distance distribution, so the X-shaped bulge is imprinted in the old stellar population, not only in younger red clump giants.
  • The retrograde fraction has been roughly stable for several gigayears after bar formation, so today's observations reflect a settled equilibrium rather than a transient state.
  • A high fraction of retrograde stars near the center naturally explains why centrally concentrated surveys find slower rotation and a rounder bulge.
  • The simulation predicts that most retrograde stars are not permanently retrograde but oscillate across the inner Lindblad resonance, so a star's current retrograde status is a snapshot rather than a fixed identity.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the paper is right, estimates of the Milky Way's accreted stellar mass that count the inner spheroid as a classical bulge would need to be scaled down; separating the secular retrograde component first is the obvious correction.
  • The paper's own comparison leaves a gap at small Galactocentric radii, where the observed retrograde fraction exceeds the isolated simulation; that region is the natural place to look for a residual merger-built component.
  • The same orbit-separation test could be applied to other old tracer populations or to barred galaxies in cosmological simulations; a universal linear retrograde-metallicity trend would strengthen the case for bar-driven angular-momentum exchange.
  • A clean test would be to measure alpha-element abundances for the retrograde bulge stars: the secular scenario requires them to be old and relatively alpha-rich, whereas a large young or alpha-poor retrograde population would point to an accreted origin.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 5 minor

Summary. The paper assembles an 8,456-star sample of bulge RR Lyrae stars with full 6D phase-space information, computes orbits in a barred Milky Way potential, and classifies stars as prograde or retrograde in the bar frame. It reports that the retrograde fraction increases toward metal-poor and centrally concentrated stars, that retrograde orbits are comparable in regularity to prograde orbits, and that RR Lyrae stars on banana orbits show a bimodal distance distribution similar to the X-shaped bulge traced by red clump stars. Comparing these observations to an isolated N-body+SPH simulation (HG1), the authors argue that the previously identified spheroidal, slowly rotating bulge component can be produced secularly by bar evolution and angular-momentum exchange, reducing the need for a classical bulge formed by mergers.

Significance. The observational dataset is a substantial advance: 8,456 bulge RR Lyrae stars with 6D kinematics, 100 Monte Carlo orbit realizations per star, a publicly available barred potential, pattern-speed robustness tests in Appendix C, and an explicit discussion of photometric-metallicity systematics. The empirical detection of a bar-frame retrograde population with a centrally concentrated, rounder spatial distribution, and the recovery of the X-shape signature through banana-orbit selection, are valuable results that stand independently of the interpretive claims. The data products and derived velocities are made available on Zenodo. If the secular-origin interpretation survives quantitative scrutiny, it would have broad implications for the role of classical bulges in the Milky Way; as it stands, however, the paper's central conclusion in Section 9 is stronger than the simulation comparison supports.

major comments (2)
  1. [Section 5.3, Fig. 9; Section 7.2; Section 4.3] The quantitative comparison between observations and the HG1 simulation does not support the strength of the secular-origin conclusion. For stars at r_GC < 0.5 kpc the observed retrograde fraction is almost 40% for RR Lyrae stars and about 35% for red giants (Fig. 9), while the oldest bulge-confined simulation particles reach only 20±1%, or 18±1% after the Eq. 14 footprint cuts (Section 7.2), and the full selected particle sample gives 14% (Section 4.3). The authors themselves state in Section 5.3 that the observed fraction is "considerably higher at rGC<0.5 in the observations than in the simulation" and that "an additional old, spheroidal classical bulge population at small Galactocentric radii" is also consistent with the data. Because the central claim of Section 9 is that the spheroidal component "can be related to the secular evolution" on the basis of this simulation, the factor-of-two shortfall in the very region where the spheroidal component is most prominent is load-bearing. A quantitative model that adds a classical-bulge component, or a revised claim limited to a secular contribution to part of the spheroidal population, is needed before the interpretive conclusion can be drawn.
  2. [Section 8.1 and Section 9; Section 4.1] The secular-origin interpretation rests on a single isolated N-body+SPH simulation (HG1), and the paper's own caveat in Section 8 concedes this: "additional investigations with a diverse set of N-body and cosmological simulations would be useful." No independent model is presented to show that the retrograde fraction, its age/metallicity trend, and its orbital stability are generic consequences of bar slowdown rather than specific to the initial conditions of HG1. The claim that the Milky Way's spherical component "can be related to the secular evolution" is therefore under-supported even setting aside the quantitative mismatch in Fig. 9. I would like to see either an additional simulation (for example, a cosmological run or a model with different initial angular-momentum distribution) or a more restricted statement that the simulation demonstrates a mechanism by which some retrograde stars can arise secularly.
minor comments (5)
  1. [Section 5.1 vs. Section 9] The percentages for the [Fe/H] < -2.0 dex sample are inconsistent between the two sections: Section 5.1 gives 40% interlopers and 41% prograde stars, while Section 9 gives 38% interlopers and 43% prograde stars. These should be harmonized to the same sample definition and rounding.
  2. [Section 7.2] The phrase "while more than44 remains prograde" is missing a percent sign and should read "more than 44% remain prograde."
  3. [Section 5.3, Fig. 9] The text says the figure shows "the dependence of Ωrot_phi on stellar age and rGC," but the y-axis of Fig. 9 is the percentage of stars with Ωrot_phi < 0. Please clarify the wording to match the plotted quantity.
  4. [Section 3.1] The sentence "which makes distraction and clear separation difficult" should read "which makes distinction and clear separation difficult."
  5. [Section 5.3] The description of the simulation binning ("a box with a size of 1000 and a step equal to 350") does not state the units or what quantity is being binned; please specify, for example the number of particles per boxcar window.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the observed retrograde fractions and orbital shapes are measured, not fitted to the simulation, and the simulation comparison openly under-predicts the central retrograde fraction.

full rationale

The paper's central observational results (rotation lag, rising retrograde fraction toward metal-poor and central stars, banana-orbit bimodality, and the spheroidal distribution of retrograde RR Lyrae stars) are derived from orbit integrations of 8456 stars in a fixed analytical barred potential. The prograde/retrograde classification is defined by the sign of Omega_phi^rot = Omega_phi^ine - Omega_P (Eq. 9), which is a measurement criterion, not a fit to the N-body simulation. The spherical shape and central concentration of retrograde stars are then measured from the data (Section 5.3, Figure 10) rather than imposed by that classification. The simulation HG1 is an independent N-body+SPH model with scaling factors adopted from prior work; no simulation parameter is tuned to reproduce the observed retrograde fractions. Indeed, the paper explicitly reports that the observed fraction is 'considerably higher at rGC<0.5 in the observations than in the simulation' and concedes that 'an additional old, spheroidal classical bulge population at small Galactocentric radii' is also consistent with the data, demonstrating that the comparison is not constructed to force the secular-origin conclusion. The cited prior work by the same group supplies data products, templates, frequency-analysis software, and the simulation itself; it is not invoked as an unverified premise or a uniqueness theorem to exclude alternatives. The interpretive claim of a secular spherical bulge is a model-based inference from measured orbital statistics, explicitly qualified by the statement that 'additional investigations with a diverse set of N-body and cosmological simulations would be useful.' No equation or fitted parameter is renamed as a prediction; the central claims retain independent observational content and are not equivalent to their inputs by construction.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The central claim rests on a small number of hand-chosen thresholds (3.5 kpc apocenter, banana frequency windows, regularity threshold) and on the adoptions of the analytic barred potential and the isolated HG1 simulation. None of these are fitted to produce the headline result, and the pattern speed is explicitly varied over a wide range in Appendix C, so the circularity burden is low. The main fragility is the transferability of the single simulation to the Milky Way.

free parameters (6)
  • Pattern speed Omega_P = 37.5 km/s/kpc (tested 24-50)
    Adopted from literature to define the bar reference frame; used to classify prograde/retrograde orbits and rotate the analytical potential. Appendix C shows results are stable across 24-50 km/s/kpc, so it is not tuned to the data.
  • Apocentric-distance interloper cut r_apo = 3.5 kpc
    Hand-chosen threshold to separate bulge stars from halo/disk interlopers, motivated by Lucey et al. (2023) and by the extent of the prograde structure. Affects the composition of the bulge sample and the reported 22% interloper fraction.
  • Banana-orbit frequency window Omega_z/Omega_x = 1.95-2.05
    Classification window inherited from Portail et al. (2015); defines the sample that shows the bimodal distance distribution. The result depends on this window choice.
  • Brezel-orbit frequency window Omega_z/Omega_x = 1.60-1.70
    Classification window from Portail et al. (2015) used to label brezel orbits in Figure 7.
  • Regular-orbit threshold log10 DeltaOmega = -1.0
    Threshold from Valluri et al. (2016) used to separate regular from chaotic orbits; affects the reported regularity percentages (52% prograde, 61% retrograde).
  • Simulation scaling factors = spatial 1.7, velocity 0.48, rotation 27 deg
    Empirical scaling used in Section 7 to map HG1 to MW photometric/kinematic footprint for the observational selection; not derived from the data and only applied in the footprint-matching part.
assumptions (5)
  • domain assumption The adopted analytical Milky Way potential (Portail et al. 2017; Sormani et al. 2022; Hunter et al. 2024) with a rotating bar at Omega_P = 37.5 km/s/kpc faithfully represents the gravitational field of the MW bulge and disk for 5 Gyr orbit integrations.
    Section 3: 'we use a publicly available code for Galactic dynamics, AGAMA... an analytical non-axisymmetric approximation of the MW and Galactic bulge model...' The orbital families and pro/retro classification are all computed in this potential; if the bar's shape, mass, or pattern speed were wrong, the orbital-based conclusions could change.
  • domain assumption The isolated N-body+SPH simulation HG1 (no mergers, no cosmological environment) is representative of the Milky Way's bulge formation and its retrograde population.
    Section 4.1: 'a high-resolution star-forming N-body+SPH simulation of a galaxy that evolves in isolation.' Section 7.2 uses it to assert the retrograde fraction stabilizes within a few Gyr after bar formation and that most retrograde particles oscillate rather than remain retrograde. The paper acknowledges this is one model and calls for diverse simulations.
  • domain assumption Photometric metallicities and distances from Prudil et al. (2025), based on VVV/OGLE photometry, are accurate enough for the metallicity binning and orbit computation; known long-period RRab photometric metallicity systematics do not change the pro/retro ratios.
    Section 5.1: 'the observed inconsistency in photometric metallicities for long-period RRab RR Lyrae stars ... is likely present in our dataset' but the authors argue the effect on distance is minimal and the prograde/retrograde ratio is unchanged by shifting the metallicity limit.
  • domain assumption Gaia astrometric quality cuts (RUWE < 1.4 and ipd_frac_multi_peak < 5) remove blends and unreliable proper motions.
    Equation 1; standard quality selection. If blending remains, proper motions and hence orbits could be corrupted for some stars.
  • standard math The frequency analysis in naif, using complex time series, correctly identifies fundamental frequencies and the sign of Omega_phi; regular orbits conserve frequencies in the barred potential.
    Section 3: complex time series defined as in Papaphilippou & Laskar (1996) and Beraldo e Silva et al. (2023); this is an established method, not ad hoc.

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Pith. "Pith review of The Galactic Bulge exploration V.: The secular spherical and X-shaped Milky Way bulge." pith.science (2026). https://pith.science/paper/UTAZNEE7

@misc{pith2026250619074,
  author       = {Pith},
  title        = {Pith review of: The Galactic Bulge exploration V.: The secular spherical and X-shaped Milky Way bulge},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/UTAZNEE7}},
  note         = {Machine review of arXiv:2506.19074}
}
abstract

In this work, we derive systemic velocities and subsequently orbits for 8456 RR~Lyrae stars. We identify interlopers from other Milky Way (MW) structures, which amount to 22 percent of the total sample. Most interlopers are associated with the halo, with the remainder linked to the Galactic disk. We confirm the previously reported lag in the rotation curve of bulge RR~Lyrae stars regardless of the removal of interlopers. Metal-rich RR~Lyrae stars' rotation patterns are consistent with that of non-variable metal-rich giants, following the MW bar, while metal-poor stars exhibit slower rotation. The analysis of orbital parameter space is used to distinguish bulge stars that, in the bar reference frame, have prograde orbits from those in retrograde orbits. We classify the prograde stars into orbital families and estimate the chaoticity (in the form of frequency drift) of their orbits. RR~Lyrae stars with banana-like orbits have a bimodal distance distribution, similar to the distance distribution seen in the metal-rich red clump stars. The fraction of stars with banana-like orbits decreases linearly with metallicity, as does the fraction of stars on prograde orbits (in the bar reference frame). The retrograde moving stars (in the bar reference frame) form a centrally concentrated nearly spherical distribution. Analyzing an $N$-body+SPH simulation, we find that some stellar particles in the central parts oscillate between retrograde and prograde orbits and only a minority stays prograde over a long period of time. Based on the simulation, the ratio between prograde and retrograde stellar particles seems to stabilize within a couple of gigayears after bar formation. The non-chaoticity of retrograde orbits and their high numbers can explain some of the spatial and kinematical features of the MW bulge that have been often associated with a classical bulge.

Figures

Figures reproduced from arXiv: 2506.19074 by the authors.

Figure 1
Figure 1. The period amplitude diagram for RRab+RRc RR Lyrae stars (RRab blue points and RRc red squares) in our final dynamical data set based on pulsation properties from the OGLE survey. spectral range covers a region mostly populated by iron (Fe i and Fe ii) and Calcium lines (from 5300 Å to 5600 Å). In total, we obtained spectra for nearly 9000 RR Lyrae stars toward the Galactic bulge. Unfortunately, not all stars had su… view at source ↗
Figure 2
Figure 2. Left: the distribution of Galactic bulge (red squares, 𝑟apo < 3.5 kpc) and interloping (blue circles, 𝑟apo > 3.5 kpc) RR Lyrae as a function of Galactocentric radius. Middle: the fraction of interloping RR Lyrae as a function of Galactocentric radius. Right: the fraction of interloping RR Lyrae in bins of photometric metallicity. The highlighted regions mark the boundaries in metallicity for the Galactic halo and di… view at source ↗
Figure 3
Figure 3. The distribution of average 𝑣GV and its dispersion 𝜎𝑣GV across the Galactic longitude bins and for different photometric metallicity cuts. The blue points represent the final dynamical data set, and the red squares stand for RR Lyrae variables with 𝑟apo < 3.5 kpc (labeled BLG in the legend). The dashed lines trace the 𝑣GV and 𝜎𝑣GV from the bar model of Shen et al. (2010) for b = 4 deg. For this Figure we use equally… view at source ↗
Figures from the paper (13 more)
Figure 4
Figure 4. Figure 4: The metallicity (top panel) and spatial distribution in Galactic coordinates (middle panel) and Cartesian coordinates (bottom panel) for RR Lyrae (blue squares) and non-variable giants (orange points) data sets. The solid white lines in the top panel depict the approxi…
Figure 5
Figure 5. Figure 5: The kinematic and orbital properties for RR Lyrae variables, non-variable giants, and stellar particles from the simulation. The top panels show the distribution of average 𝑣GV and its dispersion 𝜎𝑣GV across the Galactic longitude bins. The middle and bottom panels dis…
Figure 6
Figure 6. Figure 6: The distribution average 𝑣GV across Galactic longitude for metal￾poor ([Fe/H] < −2.0 dex) RR Lyrae variables. The blue circles and red squares represent prograde and retrograde RR Lyrae stars, respectively. Here we take bins in Galactic longitude between between −8.0 t…
Figure 7
Figure 7. Figure 7: The top panel shows the fraction of banana-orbits on metallicity for APOGEE red giants (yellow circles), BDBS red clumps (green pen￾tagons), and RR Lyrae (blue squares) data sets. The bottom panel shows the distance distribution of the RR Lyrae data set. The black hist…
Figure 8
Figure 8. Figure 8: shows a gradual increase in the number of retro￾grade stars with respect to the bar as the metallicity of a star decreases. Examining the metal-poor end ([Fe/H] < −1.0 dex) of our observational sample we notice a weak hint of a plateau around [Fe/H] ≈ −1.5 dex. The inc…
Figure 10
Figure 10. Figure 10: The spatial distribution depicted using the kernel density es￾timates of the Cartesian coordinates for our RR Lyrae bulge dataset. Blue and red contours show the distributions of prograde and retrograde RR Lyrae stars. The black solid, dashed and dotted lines represen…
Figure 9
Figure 9. Figure 9: The percentage of stars with negative Ωrot 𝜑 as a function of age (top panel), and Galactocentric spherical radius (bottom panel). The grey solid line represents the trend obtained from the simulation. Galactocentric radii (as reported in some of the previous studies, …
Figure 12
Figure 12. Figure 12: Frequency map illustrating fundamental frequencies in the Cartesian coordinate system and bar-rotating reference frame for our RR Lyrae dataset. Color-coding is used to represent positive and neg￾ative values of Ωrot 𝜑 . Major orbital families are labeled and delineat…
Figure 13
Figure 13. Figure 13: Frequency map showing fundamental frequencies in cylindrical coordinates for prograde RR Lyrae stars in the Galactic bulge dataset. The insets present 2D density maps of the face-on projection (with power-law normalization) of non-chaotic (log ΔΩ < −1.0) orbits in a r…
Figure 14
Figure 14. Figure 14: Same as [PITH_FULL_IMAGE:figures/full_fig_p017_14.png]
Figure 15
Figure 15. Figure 15: The frequency maps for the same prograde stellar particles in six simulation snapshots. As in [PITH_FULL_IMAGE:figures/full_fig_p018_15.png]
Figure 17
Figure 17. Figure 17: Frequency maps for stellar particles that oscillate between pro￾grade and retrograde orbits with respect to the bar during six analyzed snapshots. In the top panel, we see a frequency map similar to the one in [PITH_FULL_IMAGE:figures/full_fig_p019_17.png]
Figure 19
Figure 19. Figure 19: Frequency maps (top panels) and the fraction of retrograde stellar particles (bottom panels) of different ages across several snap￾shots. The top panels display the distribution of younger stellar particles in frequency maps for two different snapshots. Three groups o…

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The Galactic Bulge exploration VI.: Gaia Enceladus/Sausage RR Lyrae stars in the inner-central stellar halo of the Milky Way

    astro-ph.GA 2025-07 conditional novelty 6.0 of 10

    RR Lyrae stars in the inner-central Milky Way halo show a modest 6-9% Gaia-Enceladus-Sausage contribution, lower than at the solar neighborhood.

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Works this paper leans on

198 extracted references · 37 canonical work pages · cited by 1 Pith paper

  1. [1]

    G., Valluri , M., Shen , J., & Debattista , V

    Abbott , C. G., Valluri , M., Shen , J., & Debattista , V. P. 2017, , 470, 1526

  2. [2]

    C., Bloch , A

    Adams , F. C., Bloch , A. M., Butler , S. C., Druce , J. M., & Ketchum , J. A. 2007, , 670, 1027

  3. [3]

    A., Alves , D

    Alcock , C., Allsman , R. A., Alves , D. R., et al. 1998, , 492, 190

  4. [4]

    R., Gough-Kelly , S., Debattista , V

    Anderson , S. R., Gough-Kelly , S., Debattista , V. P., et al. 2024, , 527, 2919

  5. [5]

    2014, , 563, A60

    Antoja , T., Helmi , A., Dehnen , W., et al. 2014, , 563, A60

  6. [6]

    Ardern-Arentsen , A., Monari , G., Queiroz , A. B. A., et al. 2024, , 530, 3391

  7. [7]

    F., et al

    Arentsen , A., Starkenburg , E., Martin , N. F., et al. 2020, , 491, L11

  8. [8]

    J., & Scott , P

    Asplund , M., Grevesse , N., Sauval , A. J., & Scott , P. 2009, , 47, 481

Show all 198 references
  1. [9]

    M., Sip o cz , B

    Astropy Collaboration , Price-Whelan , A. M., Sip o cz , B. M., et al. 2018, , 156, 123

  2. [10]

    P., Tollerud , E

    Astropy Collaboration , Robitaille , T. P., Tollerud , E. J., et al. 2013, , 558, A33

  3. [11]

    2003, , 341, 1179

    Athanassoula , E. 2003, , 341, 1179

  4. [12]

    2005, , 358, 1477

    Athanassoula , E. 2005, , 358, 1477

  5. [13]

    1946, , 58, 249

    Baade , W. 1946, , 58, 249

  6. [14]

    & Gilmore , G

    Babusiaux , C. & Gilmore , G. 2005, , 358, 1309

  7. [15]

    & Price , M

    Bayes , M. & Price , M. 1763, Philosophical Transactions of the Royal Society of London Series I, 53, 370

  8. [16]

    F., Freeman , K

    Beaulieu , S. F., Freeman , K. C., Kalnajs , A. J., Saha , P., & Zhao , H. 2000, , 120, 855

  9. [17]

    & Kravtsov , A

    Belokurov , V. & Kravtsov , A. 2022, , 514, 689

  10. [18]

    C., Feltzing , S., et al

    Bensby , T., Yee , J. C., Feltzing , S., et al. 2013, , 549, A147

  11. [19]

    P., Anderson , S

    Beraldo e Silva , L., Debattista , V. P., Anderson , S. R., et al. 2023, , 955, 38

  12. [20]

    2019, , 486, 2075

    Blanco-Cuaresma , S. 2019, , 486, 2075

  13. [21]

    2014, , 569, A111

    Blanco-Cuaresma , S., Soubiran , C., Heiter , U., & Jofr \'e , P. 2014, , 569, A111

  14. [22]

    R., Bershady , M

    Blanton , M. R., Bershady , M. A., Abolfathi , B., et al. 2017, , 154, 28

  15. [23]

    2024, , 527, 12196

    Bobrick , A., Iorio , G., Belokurov , V., et al. 2024, , 527, 12196

  16. [24]

    2015, , 216, 29

    Bovy , J. 2015, , 216, 29

  17. [25]

    F., Crestani , J., Fabrizio , M., et al

    Braga , V. F., Crestani , J., Fabrizio , M., et al. 2021, , 919, 85

  18. [26]

    2021, , 506, 150

    Buder , S., Sharma , S., Kos , J., et al. 2021, , 506, 150

  19. [27]

    Butler , D., Carbon , D., & Kraft , R. P. 1976, , 210, 120

  20. [28]

    2024, , 963, L33

    Butler , E., Kunder , A., Prudil , Z., et al. 2024, , 963, L33

  21. [29]

    & Kurucz , R

    Castelli , F. & Kurucz , R. L. 2003, in Modelling of Stellar Atmospheres, ed. N. Piskunov , W. W. Weiss , & D. F. Gray , Vol. 210, A20

  22. [30]

    2009, , 320, 261

    Catelan , M. 2009, , 320, 261

  23. [31]

    K., Gerhard , O., et al

    Chatzopoulos , S., Fritz , T. K., Gerhard , O., et al. 2015, , 447, 948

  24. [32]

    Chiba , R., Friske , J. K. S., & Sch \"o nrich , R. 2021, , 500, 4710

  25. [33]

    & Sch \"o nrich , R

    Chiba , R. & Sch \"o nrich , R. 2022, , 513, 768

  26. [34]

    Clarke , J. P. & Gerhard , O. 2022, , 512, 2171

  27. [35]

    2008, , 684, 1110

    Clarkson , W., Sahu , K., Anderson , J., et al. 2008, , 684, 1110

  28. [36]

    G., Bragaglia , A., et al

    Clementini , G., Gratton , R. G., Bragaglia , A., et al. 2005, , 630, L145

  29. [37]

    2023, , 674, A18

    Clementini , G., Ripepi , V., Garofalo , A., et al. 2023, , 674, A18

  30. [38]

    R., Debattista , V

    Cole , D. R., Debattista , V. P., Erwin , P., Earp , S. W. F., & Ro s kar , R. 2014, , 445, 3352

  31. [39]

    1990, , 233, 82

    Combes , F., Debbasch , F., Friedli , D., & Pfenniger , D. 1990, , 233, 82

  32. [40]

    & Sanders , R

    Combes , F. & Sanders , R. H. 1981, , 96, 164

  33. [41]

    & Papayannopoulos , T

    Contopoulos , G. & Papayannopoulos , T. 1980, , 92, 33

  34. [42]

    F., Fabrizio , M., et al

    Crestani , J., Braga , V. F., Fabrizio , M., et al. 2021 a , , 914, 10

  35. [43]

    F., et al

    Crestani , J., Fabrizio , M., Braga , V. F., et al. 2021 b , , 908, 20

  36. [44]

    P., Carollo , C

    Debattista , V. P., Carollo , C. M., Mayer , L., & Moore , B. 2004, , 604, L93

  37. [45]

    P., Gerhard , O., & Sevenster , M

    Debattista , V. P., Gerhard , O., & Sevenster , M. N. 2002, , 334, 355

  38. [46]

    P., Mayer , L., Carollo , C

    Debattista , V. P., Mayer , L., Carollo , C. M., et al. 2006, , 645, 209

  39. [47]

    P., Ness , M., Gonzalez , O

    Debattista , V. P., Ness , M., Gonzalez , O. A., et al. 2017, , 469, 1587

  40. [48]

    Debattista , V. P. & Sellwood , J. A. 1998, , 493, L5

  41. [49]

    2023, , 518, 2712

    Dehnen , W., Semczuk , M., & Sch \"o nrich , R. 2023, , 518, 2712

  42. [50]

    2013, , 776, L19

    D \'e k \'a ny , I., Minniti , D., Catelan , M., et al. 2013, , 776, L19

  43. [51]

    R., et al

    D'Orazi , V., Storm , N., Casey , A. R., et al. 2024, , 531, 137

  44. [52]

    2020, , 498, 5629

    Du , H., Mao , S., Athanassoula , E., Shen , J., & Pietrukowicz , P. 2020, , 498, 5629

  45. [53]

    G., Hauser , M

    Dwek , E., Arendt , R. G., Hauser , M. G., et al. 1995, , 445, 716

  46. [54]

    1965, Trudy Astrofizicheskogo Instituta Alma-Ata, 5, 87

    Einasto , J. 1965, Trudy Astrofizicheskogo Instituta Alma-Ata, 5, 87

  47. [55]

    Erkal , D., Belokurov , V., Laporte , C. F. P., et al. 2019, , 487, 2685

  48. [56]

    F., et al

    Fabrizio , M., Bono , G., Braga , V. F., et al. 2019, , 882, 169

  49. [57]

    F., Crestani , J., et al

    Fabrizio , M., Braga , V. F., Crestani , J., et al. 2021, , 919, 118

  50. [58]

    Fiteni , K., Caruana , J., Amarante , J. A. S., Debattista , V. P., & Beraldo e Silva , L. 2021, , 503, 1418

  51. [59]

    W., Lang , D., & Goodman , J

    Foreman-Mackey , D., Hogg , D. W., Lang , D., & Goodman , J. 2013, , 125, 306

  52. [60]

    2018, , 616, A180

    Fragkoudi , F., Di Matteo , P., Haywood , M., et al. 2018, , 616, A180

  53. [61]

    Fragkoudi , F., Grand , R. J. J., Pakmor , R., et al. 2020, , 494, 5936

  54. [62]

    Gaia Collaboration , Prusti , T., de Bruijne , J. H. J., et al. 2016, , 595, A1

  55. [63]

    Gaia Collaboration , Vallenari , A., Brown , A. G. A., et al. 2023, , 674, A1

  56. [64]

    P., Robin , A

    Gardner , E., Debattista , V. P., Robin , A. C., V \'a squez , S., & Zoccali , M. 2014, , 438, 3275

  57. [65]

    A., Rejkuba , M., Zoccali , M., et al

    Gonzalez , O. A., Rejkuba , M., Zoccali , M., et al. 2011, , 530, A54

  58. [66]

    A., Zoccali , M., Vasquez , S., et al

    Gonzalez , O. A., Zoccali , M., Vasquez , S., et al. 2015, , 584, A46

  59. [67]

    P., Clarkson , W

    Gough-Kelly , S., Debattista , V. P., Clarkson , W. I., et al. 2022, , 509, 4829

  60. [68]

    G., Tornambe , A., & Ortolani , S

    Gratton , R. G., Tornambe , A., & Ortolani , S. 1986, , 169, 111

  61. [69]

    2015, , 449, L113

    Hajdu , G., Catelan , M., Jurcsik , J., et al. 2015, , 449, L113

  62. [70]

    K., & Jurcsik , J

    Hajdu , G., D \'e k \'a ny , I., Catelan , M., Grebel , E. K., & Jurcsik , J. 2018, , 857, 55

  63. [71]

    2021, , 915, 50

    Hajdu , G., Pietrzy \'n ski , G., Jurcsik , J., et al. 2021, , 915, 50

  64. [72]

    2025, , 985, 32

    Han , X., Wang , H.-F., Carraro , G., et al. 2025, , 985, 32

  65. [73]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357–362

  66. [74]

    S., & Pe \ n arrubia , J

    Horta , D., Petersen , M. S., & Pe \ n arrubia , J. 2025, , 538, 998

  67. [75]

    P., Mackereth , J

    Horta , D., Schiavon , R. P., Mackereth , J. T., et al. 2021, , 500, 1385

  68. [76]

    D., Rich , R

    Howard , C. D., Rich , R. M., Clarkson , W., et al. 2009, , 702, L153

  69. [77]

    D., Rich , R

    Howard , C. D., Rich , R. M., Reitzel , D. B., et al. 2008, , 688, 1060

  70. [78]

    H., Sormani , M

    Hunter , G. H., Sormani , M. C., Beckmann , J. P., et al. 2024, , 692, A216

  71. [79]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90

  72. [80]

    & Belokurov , V

    Iorio , G. & Belokurov , V. 2021, , 502, 5686

  73. [81]

    I., Rich , R

    Johnson , C. I., Rich , R. M., Simion , I. T., et al. 2022, , 515, 1469

  74. [82]

    I., Marchetti , T., et al

    Joyce , M., Johnson , C. I., Marchetti , T., et al. 2023, , 946, 28

  75. [83]

    & Hajdu , G

    Jurcsik , J. & Hajdu , G. 2023, , 525, 3486

  76. [84]

    2021, , 505, 2468

    Jurcsik , J., Hajdu , G., & Juh \'a sz , \'A . 2021, , 505, 2468

  77. [85]

    2023, , 674, A5

    Katz , D., Sartoretti , P., Guerrier , A., et al. 2023, , 674, A5

  78. [86]

    W., & Thompson , I

    Koch , A., McWilliam , A., Preston , G. W., & Thompson , I. B. 2016, , 587, A124

  79. [87]

    & Kennicutt , Robert C., J

    Kormendy , J. & Kennicutt , Robert C., J. 2004, , 42, 603

  80. [88]

    M., et al

    Kunder , A., Koch , A., Rich , R. M., et al. 2012, , 143, 57

  81. [89]

    M., et al

    Kunder , A., P \'e rez-Villegas , A., Rich , R. M., et al. 2020, , 159, 270

  82. [90]

    2024, , 168, 139

    Kunder , A., Prudil , Z., Skaggs , C., et al. 2024, , 168, 139

  83. [91]

    M., Koch , A., et al

    Kunder , A., Rich , R. M., Koch , A., et al. 2016, , 821, L25

  84. [92]

    1993, Physica D: Nonlinear Phenomena, 67, 257

    Laskar, J. 1993, Physica D: Nonlinear Phenomena, 67, 257

  85. [93]

    C., Hanson , R

    Layden , A. C., Hanson , R. B., Hawley , S. L., Klemola , A. R., & Hanley , C. J. 1996, , 112, 2110

  86. [94]

    W., Bovy , J., Mackereth , J

    Leung , H. W., Bovy , J., Mackereth , J. T., et al. 2023, , 519, 948

  87. [95]

    2021, , 907, 47

    Lim , D., Lee , Y.-W., Koch , A., et al. 2021, , 907, 47

  88. [96]

    2021, , 501, 5981

    Lucey , M., Hawkins , K., Ness , M., et al. 2021, , 501, 5981

  89. [97]

    2022, , 509, 122

    Lucey , M., Hawkins , K., Ness , M., et al. 2022, , 509, 122

  90. [98]

    Lucey , M., Pearson , S., Hunt , J. A. S., et al. 2023, , 520, 4779

  91. [99]

    Lyapunov, A. M. 1992, International Journal of Control, 55, 531

  92. [100]

    & Kalnajs , A

    Lynden-Bell , D. & Kalnajs , A. J. 1972, , 157, 1

  93. [101]

    T., Bovy , J., Leung , H

    Mackereth , J. T., Bovy , J., Leung , H. W., et al. 2019, , 489, 176

  94. [102]

    R., Schiavon , R

    Majewski , S. R., Schiavon , R. P., Frinchaboy , P. M., et al. 2017, , 154, 94

  95. [103]

    I., et al

    Marchetti , T., Joyce , M., Johnson , C. I., et al. 2024, , 682, A96

  96. [104]

    2006, , 637, 214

    Martinez-Valpuesta , I., Shlosman , I., & Heller , C. 2006, , 637, 214

  97. [105]

    2023, , 680, A20

    Massari , D., Aguado-Agelet , F., Monelli , M., et al. 2023, , 680, A20

  98. [106]

    McMillan , P. J. 2017, , 465, 76

  99. [107]

    & Rich , R

    McWilliam , A. & Rich , R. M. 1994, , 91, 749

  100. [108]

    & Zoccali , M

    McWilliam , A. & Zoccali , M. 2010, , 724, 1491

  101. [109]

    & Sellwood , J

    Merritt , D. & Sellwood , J. A. 1994, , 425, 551

  102. [110]

    1998, in The Central Regions of the Galaxy and Galaxies, ed

    Minniti , D., Alcock , C., Alves , D., et al. 1998, in The Central Regions of the Galaxy and Galaxies, ed. Y. Sofue , Vol. 184, 123

  103. [111]

    W., Emerson , J

    Minniti , D., Lucas , P. W., Emerson , J. P., et al. 2010, , 15, 433

  104. [112]

    Minniti , D., White , S. D. M., Olszewski , E. W., & Hill , J. M. 1992, , 393, L47

  105. [113]

    M., Udalski , A., Gould , A., Fouqu \'e , P., & Stanek , K

    Nataf , D. M., Udalski , A., Gould , A., Fouqu \'e , P., & Stanek , K. Z. 2010, , 721, L28

  106. [114]

    2013 a , , 430, 836

    Ness , M., Freeman , K., Athanassoula , E., et al. 2013 a , , 430, 836

  107. [115]

    2013 b , , 432, 2092

    Ness , M., Freeman , K., Athanassoula , E., et al. 2013 b , , 432, 2092

  108. [116]

    2012, , 756, 22

    Ness , M., Freeman , K., Athanassoula , E., et al. 2012, , 756, 22

  109. [117]

    A., et al

    Ness , M., Zasowski , G., Johnson , J. A., et al. 2016, , 819, 2

  110. [118]

    2018, , 480, 1229

    Netzel , H., Smolec , R., Soszy \'n ski , I., & Udalski , A. 2018, , 480, 1229

  111. [119]

    2024, , 687, A312

    Olivares Carvajal , J., Zoccali , M., De Leo , M., et al. 2024, , 687, A312

  112. [120]

    1995, , 377, 701

    Ortolani , S., Renzini , A., Gilmozzi , R., et al. 1995, , 377, 701

  113. [121]

    & Laskar , J

    Papaphilippou , Y. & Laskar , J. 1996, , 307, 427

  114. [122]

    & Laskar , J

    Papaphilippou , Y. & Laskar , J. 1998, , 329, 451

  115. [123]

    A., Skokos , C., & Athanassoula , E

    Patsis , P. A., Skokos , C., & Athanassoula , E. 2002, , 337, 578

  116. [124]

    & Granger, B

    P\'erez, F. & Granger, B. E. 2007, Computing in Science and Engineering, 9, 21

  117. [125]

    & Friedli , D

    Pfenniger , D. & Friedli , D. 1991, , 252, 75

  118. [126]

    2015, , 811, 113

    Pietrukowicz , P., Koz owski , S., Skowron , J., et al. 2015, , 811, 113

  119. [127]

    2012, , 750, 169

    Pietrukowicz , P., Udalski , A., Soszy \'n ski , I., et al. 2012, , 750, 169

  120. [128]

    Pontzen , A., Ro s kar , R., Stinson , G., & Woods , R. 2013

  121. [129]

    2017, , 465, 1621

    Portail , M., Gerhard , O., Wegg , C., & Ness , M. 2017, , 465, 1621

  122. [130]

    2015, , 450, L66

    Portail , M., Wegg , C., & Gerhard , O. 2015, , 450, L66

  123. [131]

    K., et al

    Prudil , Z., D \'e k \'a ny , I., Grebel , E. K., et al. 2019 a , , 487, 3270

  124. [132]

    K., & Kunder , A

    Prudil , Z., D \'e k \'a ny , I., Grebel , E. K., & Kunder , A. 2020, , 492, 3408

  125. [133]

    2021, , 648, A78

    Prudil , Z., Hanke , M., Lemasle , B., et al. 2021, , 648, A78

  126. [134]

    J., Lemasle , B., et al

    Prudil , Z., Koch-Hansen , A. J., Lemasle , B., et al. 2022, , 664, A148

  127. [135]

    2025, , 695, A211

    Prudil , Z., Kunder , A., Beraldo e Silva , L., et al. 2025, , 695, A211

  128. [136]

    Prudil , Z., Kunder , A., D \'e k \'a ny , I., & Koch-Hansen , A. J. 2024 a , , 684, A176

  129. [137]

    & Skarka , M

    Prudil , Z. & Skarka , M. 2017, , 466, 2602

  130. [138]

    K., & Lee , C

    Prudil , Z., Skarka , M., Li s ka , J., Grebel , E. K., & Lee , C. U. 2019 b , , 487, L1

  131. [139]

    J., & D \'e k \'a ny , I

    Prudil , Z., Smolec , R., Kunder , A., Koch-Hansen , A. J., & D \'e k \'a ny , I. 2024 b , , 685, A153

  132. [140]

    2017, , 465, 4074

    Prudil , Z., Smolec , R., Skarka , M., & Netzel , H. 2017, , 465, 4074

  133. [141]

    Queiroz , A. B. A., Anders , F., Chiappini , C., et al. 2020, , 638, A76

  134. [142]

    Queiroz , A. B. A., Anders , F., Santiago , B. X., et al. 2018, , 476, 2556

  135. [143]

    Queiroz , A. B. A., Chiappini , C., Perez-Villegas , A., et al. 2021, , 656, A156

  136. [144]

    Quillen , A. C. 2002, , 124, 722

  137. [145]

    C., Minchev , I., Sharma , S., Qin , Y.-J., & Di Matteo , P

    Quillen , A. C., Minchev , I., Sharma , S., Qin , Y.-J., & Di Matteo , P. 2014, , 437, 1284

  138. [146]

    A., James , R

    Raha , N., Sellwood , J. A., James , R. A., & Kahn , F. D. 1991, , 352, 411

  139. [147]

    2018, , 863, 16

    Renzini , A., Gennaro , M., Zoccali , M., et al. 2018, , 863, 16

  140. [148]

    Rich , R. M. 1988, , 95, 828

  141. [149]

    M., Johnson , C

    Rich , R. M., Johnson , C. I., Young , M., et al. 2020, , 499, 2340

  142. [150]

    M., Reitzel , D

    Rich , R. M., Reitzel , D. B., Howard , C. D., & Zhao , H. 2007, , 658, L29

  143. [151]

    2022, , 941, 45

    Rix , H.-W., Chandra , V., Andrae , R., et al. 2022, , 941, 45

  144. [152]

    2024, , 975, 293

    Rix , H.-W., Chandra , V., Zasowski , G., et al. 2024, , 975, 293

  145. [153]

    2014, , 569, A103

    Rojas-Arriagada , A., Recio-Blanco , A., Hill , V., et al. 2014, , 569, A103

  146. [154]

    2020, , 499, 1037

    Rojas-Arriagada , A., Zasowski , G., Schultheis , M., et al. 2020, , 499, 1037

  147. [155]

    & Girardi , L

    Salaris , M. & Girardi , L. 2002, , 337, 332

  148. [156]

    M., Gough-Kelly , S., Debattista , V

    San Martin Fernandez , L. M., Gough-Kelly , S., Debattista , V. P., et al. 2025, , 540, 2506

  149. [157]

    L., Kawata , D., Matsunaga , N., et al

    Sanders , J. L., Kawata , D., Matsunaga , N., et al. 2024, , 530, 2972

  150. [158]

    L., Smith , L., & Evans , N

    Sanders , J. L., Smith , L., & Evans , N. W. 2019, , 488, 4552

  151. [159]

    X., Brauer , D

    Santiago , B. X., Brauer , D. E., Anders , F., et al. 2016, , 585, A42

  152. [160]

    2020, , 641, A96

    Savino , A., Koch , A., Prudil , Z., Kunder , A., & Smolec , R. 2020, , 641, A96

  153. [161]

    Sellwood , J. A. & Gerhard , O. 2020, , 495, 3175

  154. [162]

    2022, , 509, 4532

    Semczuk , M., Dehnen , W., Sch \"o nrich , R., & Athanassoula , E. 2022, , 509, 4532

  155. [163]

    M., Kormendy , J., et al

    Shen , J., Rich , R. M., Kormendy , J., et al. 2010, , 720, L72

  156. [164]

    T., Belokurov , V., Irwin , M., et al

    Simion , I. T., Belokurov , V., Irwin , M., et al. 2017, , 471, 4323

  157. [165]

    2020, , 494, 1237

    Skarka , M., Prudil , Z., & Jurcsik , J. 2020, , 494, 1237

  158. [166]

    W., Chadid , M., & Adam \'o w , M

    Sneden , C., Preston , G. W., Chadid , M., & Adam \'o w , M. 2017, , 848, 68

  159. [167]

    Sneden , C. A. 1973, PhD thesis, THE UNIVERSITY OF TEXAS AT AUSTIN

  160. [168]

    C., Binney , J., & Magorrian , J

    Sormani , M. C., Binney , J., & Magorrian , J. 2015, , 454, 1818

  161. [169]

    C., Gerhard , O., Portail , M., Vasiliev , E., & Clarke , J

    Sormani , M. C., Gerhard , O., Portail , M., Vasiliev , E., & Clarke , J. 2022, , 514, L1

  162. [170]

    C., Magorrian , J., Nogueras-Lara , F., et al

    Sormani , M. C., Magorrian , J., Nogueras-Lara , F., et al. 2020, , 499, 7

  163. [171]

    Z., Mateo , M., Udalski , A., et al

    Stanek , K. Z., Mateo , M., Udalski , A., et al. 1994, , 429, L73

  164. [172]

    Z., Udalski , A., Szyma \'N ski , M., et al

    Stanek , K. Z., Udalski , A., Szyma \'N ski , M., et al. 1997, , 477, 163

  165. [173]

    2022, , 941, 109

    Tahmasebzadeh , B., Zhu , L., Shen , J., Gerhard , O., & van de Ven , G. 2022, , 941, 109

  166. [174]

    & Weinberg , M

    Tremaine , S. & Weinberg , M. D. 1984, , 282, L5

  167. [175]

    P., Quinn , T., & Moore , B

    Valluri , M., Debattista , V. P., Quinn , T., & Moore , B. 2010, , 403, 525

  168. [176]

    Valluri , M., Shen , J., Abbott , C., & Debattista , V. P. 2016, , 818, 141

  169. [177]

    1932, , 6, 163

    van Gent , H. 1932, , 6, 163

  170. [178]

    1933, , 7, 21

    van Gent , H. 1933, , 7, 21

  171. [179]

    2013, , 434, 3174

    Vasiliev , E. 2013, , 434, 3174

  172. [180]

    2019, , 482, 1525

    Vasiliev , E. 2019, , 482, 1525

  173. [181]

    E., et al

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261

  174. [182]

    2024, , 528, 3576

    Vislosky , E., Minchev , I., Khoperskov , S., et al. 2024, , 528, 3576

  175. [183]

    W., Stadel , J., & Quinn , T

    Wadsley , J. W., Stadel , J., & Quinn , T. 2004, , 9, 137

  176. [184]

    Walker , A. R. & Terndrup , D. M. 1991, , 378, 119

  177. [185]

    & Gerhard , O

    Wegg , C. & Gerhard , O. 2013, , 435, 1874

  178. [186]

    2019, , 485, 3296

    Wegg , C., Gerhard , O., & Bieth , M. 2019, , 485, 3296

  179. [187]

    L., Arendt , R

    Weiland , J. L., Arendt , R. G., Berriman , G. B., et al. 1994, , 425, L81

  180. [188]

    C., Hearty , F

    Wilson , J. C., Hearty , F. R., Skrutskie , M. F., et al. 2019, , 131, 055001

  181. [189]

    M., Gerhard , O

    Wylie , S. M., Gerhard , O. E., Ness , M. K., et al. 2021, , 653, A143

  182. [190]

    Wyse , R. F. G., Gilmore , G., & Franx , M. 1997, , 35, 637

  183. [191]

    M., Nataf , D

    Xiang , K. M., Nataf , D. M., Athanassoula , E., et al. 2021, , 909, 125

  184. [192]

    2025, arXiv e-prints, arXiv:2504.06720

    Zhang , H., Iorio , G., Belokurov , V., et al. 2025, arXiv e-prints, arXiv:2504.06720

  185. [193]

    C., & Casetti-Dinescu , D

    Zinn , R., Chen , X., Layden , A. C., & Casetti-Dinescu , D. I. 2020, , 492, 2161

  186. [194]

    A., Vasquez , S., et al

    Zoccali , M., Gonzalez , O. A., Vasquez , S., et al. 2014, , 562, A66

  187. [195]

    2008, , 486, 177

    Zoccali , M., Hill , V., Lecureur , A., et al. 2008, , 486, 177

  188. [196]

    A., et al

    Zoccali , M., Vasquez , S., Gonzalez , O. A., et al. 2017, , 599, A12

  189. [197]

    , " * write output.state after.block = add.period write newline

    ENTRY address archiveprefix author booktitle chapter edition editor howpublished institution eprint journal key month note number organization pages publisher school series title type volume year label extra.label sort.label short.list INTEGERS output.state before.all mid.sent...

  190. [198]

    write newline

    " write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 gl...

Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.