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A&A
Volume 696, April 2025
Article Number L19
Number of page(s) 7
Section Letters to the Editor
DOI https://doi.org/10.1051/0004-6361/202453610
Published online 25 April 2025

© The Authors 2025

Licence Creative CommonsOpen Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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1. Introduction

During its formation, the Milky Way accreted and merged many satellites (Johnston et al. 2008). The resultant tidally stripped stellar systems, such as globular clusters and dwarf galaxies, left behind plenty of stars, which orbit the Milky Way with similar kinematic properties as their progenitors (Helmi 2020). In this way, these stellar streams record the merging history of the Milky Way. Since the discovery of the Sagittarius dwarf galaxy by Ibata et al. (1994) and its tidal stream (Ibata et al. 2001; Majewski et al. 2003) two decades ago, around 200 stellar streams have been found (Mateu et al. 2018; Ibata et al. 2024). With the help in particular of deep photometric surveys such as the SDSS (York et al. 2000), Pan-STARRS1 (Chambers et al. 2016), and DES (Dark Energy Survey Collaboration 2016), numerous cold streams have been discovered from the field stars with the matched filter method (Rockosi et al. 2002; Grillmair & Johnson 2006; Grillmair & Dionatos 2006; Grillmair 2006, 2009; Grillmair et al. 2013; Grillmair 2014; Shipp et al. 2018; Grillmair 2022). With precise proper motions provided by Gaia mission, Malhan & Ibata (2018) developed a powerful method and discovered many thin weak streams, that were previously flooded in the field stars (Malhan et al. 2019). More recently, Tian et al. (2024) tried to remove the nearby field stars and discovered a distant stream around 25 kpc. Moreover, combining the radial velocities (RVs) from spectroscopic surveys, more diffused substructures have been discovered in the phase space (Koppelman et al. 2018; Yang et al. 2019; Dodd et al. 2023; Malhan & Rix 2024).

Even more interestingly, many of those merged stellar systems did not fall into the Milky Way completely randomly, but in groups. Now we know that many globular clusters are associated with the Sagittarius system, including Arp2, Berkeley 29, M 54, NGC 5634, Pal 12, Terzan 7, Terzan 8, and Whiting-1 (Bellazzini et al. 2008; Carballo-Bello et al. 2014; Dinescu et al. 2000; Martínez-Delgado et al. 2002; Massari et al. 2019; Nie et al. 2022; Vasiliev 2019). With kinematic information, Massari et al. (2019) studied the formation of the globular clusters in the Milky Way. They found that 35% globular clusters were associated with merging events during the formation of the Milky Way. Meanwhile, many of the dwarf galaxies are located in a very thin plane that is almost perpendicular to the Galactic disk plane. What is more, Pawlowski et al. (2012) showed that many young halo clusters and streams are also associated with a correlated population, which is a vast structure, known as the Vast POlar Structure (VPOS), composed of many dwarf galaxies orbiting in a common polar plane. However, the nature of this structure remains debated. Riley & Strigari (2020) examined the orbit normals of globular clusters and stellar streams and found no evidence of significant clustering.

To study the assemble history of the Milky Way with those streams, spectroscopic observations are necessary. Spectroscopic surveys, such as LAMOST (Liu et al. 2020), APOGEE (Wilson et al. 2019), S5 (Li et al. 2019), and H3 (Conroy et al. 2019), have been proposed to observe the member stars of those known streams and obtain the chemical information and RVs. Combining H3 data with the proper motions from Gaia, Naidu et al. (2020) reconstructed the formation history of the halo and found that Gaia-Sausage-Enceladus (Helmi et al. 2018) dominates the inner halo with a galactocentric distance of r < 25 kpc, while the Sagittarius system dominates the outer part. More interesting still is that more than 95% of their samples are linked to the merging substructures, which indicates that the halo has been built from merged dwarf galaxies and the disk heating. Their results proved again that the outer halo is highly structured.

As a result, a key question is whether all the satellites have been discovered. Koposov et al. (2008) showed that the luminosity function of the satellites can be described by a single power law, ranging from MV = −2 to the luminosity of the LMC. However, the number of currently discovered satellites is much less than that predicted by the simulations; this is known as the ‘missing satellites’ problem (Klypin et al. 1999). One possible explanation is that some of those missing satellites have been fully disrupted. Because of this, there should be plenty of remnants, such as diffuse streams or clouds, left in the Milky Way. The Orphan stream is an example that many studies have concluded originated from an ultra-faint dwarf galaxy (Grillmair 2006; Sales et al. 2008). It is important to trace these merging events, especially those that originated from merged dwarf galaxies with a low surface density. However, current methods strongly limit the discovery of those faint substructures.

To this end, we focus on fainter substructures or ones with low surface densities, that have possibly been ignored or that are difficult to discover in previous work. We apply the similar method of Tian et al. (2024) to Gaia DR3 and discover a long new stream. This Letter is constructed as follows. We briefly introduce the data selection and the method in Section 2. The properties of the new stream are introduced in the Section 3. Finally, we summarize the results in the Section 4.

2. Data and method

In a small sky coverage, the stream member stars will have similar distances and velocities because all of them share a unique orbit. The member stars will be in the form of overdensities on the sky within corresponding proper motion ranges. The challenge is that the low number of member stars will make the stream flooded in the field stars. Thus, a very efficient way is needed to remove the contaminations of the field stars, especially the disk stars, which have a number density a few orders higher than that of the halo. This will significantly enhance the signal of the streams (Tian et al. 2024).

Following Tian et al. (2024), we used the data from Gaia DR3 to reveal the substructures in the halo. Here we briefly introduce the steps. Focusing on the substructures in the halo, especially those at high latitude, we first selected the stars with the following criteria.

  1. ω < 0.1 mas,

  2. σμα* < 0.2 mas yr−1 and σμδ < 0.2 mas yr−1,

  3. RUWE < 1.2,

where ω is the parallax, σα* and σδ are the uncertainties of the proper motions, and RUWE is the renormalized unit weight error.

The first criterion removes most of the nearby stars; however, a small fraction of distant stars with larger parallax uncertainties will be also removed. We did not correct the zero point of the parallax, which did not affect the final results, because the parallax was only used for removing the nearby stars. The second criterion ensures that the proper measurements of the selected stars are accurate. This will remove most of the fainter stars with G > 19. In this way, the member stars from a unique stream will stay in a smaller range of proper motion. The last criterion was used to make sure that most of the samples comprise single stars.

3. The new stream

To figure out the substructure candidates, we sliced those selected stars according to the proper motions in both the α and δ directions, and collected the overdensities on the sky, which have high probabilities of being streams.

3.1. Significance

Based on the discussion above, here we report a significant new stellar stream in the northern hemisphere with proper motions of 0.5 < μα* < 1.5 mas yr−1 and −0.5 < μδ < 0.5 mas yr−1. Figure 1 shows the density distribution of all the stars that satisfy the selection criteria, including the constraints on the proper motions. The new stream candidate is located from the top, (l, b) = (270° ,45° ), to the bottom right, (l, b) = (30° ,45° ), which is around 110 degrees long. Compared with the stellar stream library galstreams (Mateu et al. 2018), we find that this candidate does not overlap with any previously identified streams in the space, especially ones originated from dwarf galaxies such as the Orphan Stream (Belokurov et al. 2007; Koposov et al. 2023), the Cetus-Palca Stream (Newberg et al. 2009; Thomas & Battaglia 2022; Chang et al. 2020; Yuan et al. 2022), and the LMS-1 stream (Yuan et al. 2020; Malhan et al. 2021), as is shown in Figure 1.

thumbnail Fig. 1.

Density distribution of the selected stars over the northern hemisphere. The orbits of four streams are represented by the solid lines, which are provided by Mateu et al. (2018) and Chang et al. (2020). The globular cluster Pyxis is marked with red arrow with ( l , b ) = ( 261 . ° 32 , 7 . ° 00 ) $ (l,b)=(261{{{\overset{\circ}{.}}}}32, 7{{{\overset{\circ}{.}}}}00) $.

Following Tian et al. (2024), we also used the package gala1 (Price-Whelan 2017) to rotate the coordinates from the equatorial frame to a new one (ϕ1, ϕ2), making the stream run along the equator in the new frame (ϕ1, ϕ2), i.e. ϕ2 = 0°. The stream is around 110 degrees long, from ϕ1 = −45° to 65°2, as is represented by the shadow region in Figure A.1. Fitting the latitude distribution with a Gaussian distribution, we find that the signal-to-noise ratio of the stream is around 19.6. The half width (1σϕ2) is around 2 . ° 57 ± 0 . ° 52 $ 2{{{\overset{\circ}{.}}}}57\pm0{{{\overset{\circ}{.}}}}52 $. The background is around H = 12.54 for each latitude bin with a size of 1°, which indicates the contamination of the field stars in each bin on average. Next, we selected all 290 stars within |ϕ2|< 5° (around 2σ) as the member candidates, with around H * 10 bins = 125 stars from contamination.

3.2. Geometric property

Cross-matching with the spectroscopic data, we obtained spectra of 22 giant stars in total: 20 stars from LAMOST DR9 and 2 from the DESI early data release. The top panel of Figure C.1 shows the distribution of the RV versus the longitude, ϕ1, of 20 common stars. The other two stars from LAMOST are not shown with RVs of around −230 km s−1 and metallicity lower than −2. All 20 common stars were selected as member candidates to study the properties of the stream. The metallicity of those common stars has a larger variance, from −1.8 to −0.7, much larger than the uncertainties of ∼0.1 dex. What should be noticed is that all of those common stars are located on the right part of the stream because of the sky coverages of LAMOST and DESI.

First, we estimated the metallicity of the stream with the median value of those 20 member stars, [Fe/H] = −1.3. Then we tried to fit the distribution in the color-magnitude diagram (CMD) of all the member stars using the isochrone with a metallicity and age of ([Fe/H], log10 τ) = (−1.3, 10.08). With the package dustmaps (Green 2018), we corrected the extinction with the dust map obtained by Planck Collaboration Int. XXIX. (2016) and the extinction coefficients of Gaia bands provided by Wang & Chen (2019); that is, 2.489, 3.161, and 1.858 for G, BP, and RP, respectively. Then the distance modulus was constrained as 𝒟ℳ = 17.19 (diso = 27.42 kpc). Figure B.1 represents the distributions in CMD of the stars within different longitude ranges from −45° to 65° with a step of 22°. The selected common stars with LAMOST and DESI are marked with red and magenta symbols, respectively. From the middle and rightmost panels, there are two stars significantly offset from the fit isochrone, which are highlighted by the open circle in Figures C.1 and B.1. Those two stars are not considered as member stars of the stream in the following discussion. Of note is that there are no classical distance tracers among the members, such as RR Lyrae stars or blue horizontal branch stars, so here we adopt the distance of diso = 27.42 kpc for all the member stars. According to the position of the possible red horizontal branch stars, approximately located at (BP − RP, G) = (0.8, 17.6), which is marked with the horizontal dashed line in each panel, there is not a significant gradient versus the longitude, ϕ1. In this way, we first estimated the width of the stream with diso * σϕ2 = 1.23 kpc. The larger variance of the metallicity and the width discussed above suggest that the stream possibly originates from a dwarf galaxy, rather than a globular cluster.

3.3. Kinematic property

Considering most of the member candidate stars without spectroscopic observation, we only investigated the properties of the tangential velocities, which are perpendicular to the line of sight. The bottom panel of Figure C.1 shows the distribution of the tangential velocities after the correction of all the member candidate stars with G < 18. The shadow region represent the ranges caused by the proper motion selection. We find that the dispersion of the tangential velocity perpendicular to the stream is around 30.7 km s−1 for all those members with G < 18. The dispersion is an order higher than that of a cold stellar stream formed from a globular cluster, such as 2.1 ± 0.3 km s−1 for the GD-1 stream (Gialluca et al. 2021). Considering the maximum uncertainties of proper motion, 0.2 mas yr−1, the contribution to the dispersion is 4.74 * d * σμ ∼ 16.5 km s−1. Assuming a median proper motion of 1 mas yr−1 and a relative distance uncertainty of 10%, the distance uncertainty will contribute ∼13.0 km s−1. Then the intrinsic dispersion can be estimated by (30.72 − 16.52 − 13.02)0.5 = 22.4 km s−1, which is still an order higher than that of the cold stream and almost all the globular clusters3 (Harris 1996, 2010 version). The larger tangential velocity dispersion also suggests that the stream is formed from a disrupted dwarf galaxy. Considering that the stream is not orbiting a great circle on the sky, which will enlarge the dispersion of all the member candidates, we also checked the dispersion in different longitude ranges as represented by the green symbols, and we found that the dispersion is still significant enough in each subsample.

3.4. Origination

The large width of 1.23 kpc and the velocity dispersion of 22.4 km s−1 indicate that the stream originated from a dwarf galaxy. The stellar mass of its progenitor dwarf galaxy can be estimated as M* ∼ 2.0 × 107 M⊙ with the universal metallicity–mass relation provided by Kirby et al. (2013), adopting the metallicity of −1.3. That suggests a massive progenitor of a dwarf galaxy, which is smaller than the LMC, SMC, and the Sagittarius system, and comparable with that of the Fornax spheroidal dwarf galaxy. It is important to note that this relation was derived from dwarf galaxies in the Local Group, with a dispersion of 0.17. Meanwhile, the metallicity-mass relation evolves such that higher-redshift galaxies of a similar mass tend to be more metal-poor (Erb et al. 2006; Zahid et al. 2013; Henry et al. 2013).

To further investigate its origins, we integrated the orbit of the common stars with full information forward and backward with the package AGAMA (Vasiliev 2019). We represent the orbits in Figure 2 with gray lines. The potential of the Milky Way is assumed to be composed of three components: a Dehnen bulge, a Miyamoto-Nagai disk, and an NFW halo. The masses of those three parts are 2.0 × 1010 M⊙, 5.0 × 1010 M⊙, and 5.5 × 1011 M⊙, respectively. The scale radii were set 1.0 kpc, 3.0 kpc, and 15.0 kpc, then the total mass enclosed within 20 kpc was around 2.1 × 1011 M⊙. The eccentricity and pericenter distance were ∼0.7 and ∼24 kpc, respectively. The positions of the globular clusters (Vasiliev 2019) and dwarf galaxies (Drlica-Wagner et al. 2020) are also represented by the blue and yellow dots. The LMC and SMC are highlighted with larger yellow pentagons. From the sky distribution, we find that many dwarf galaxies and distant globular clusters are located on the orbit of the stream, as is shown in the left panel of Figure 2.

thumbnail Fig. 2.

Left: sky projection of the common stars, globular clusters, and dwarf galaxies represented by squares, blue dots, and yellow dots, respectively. The globular cluster Pyxis and LMC/SMC are highlighted with a larger blue dot and yellow pentagons. All globular clusters and dwarf galaxies with distances larger than 20 kpc are highlighted with a solid black edge. The integrated orbits of those stars with full 6D information are represented by the gray lines. Right: Direction distribution of the orbit normals of those common stars, distant globular clusters and dwarf galaxies with full 6D information. The symbols are the same as in the left panel. The shadow region represents the direction of the normal of the VPOS with a longitude between 150° and 210° and a latitude between −30° and 30°.

This is also proved by the orbit direction distribution in the right panel of Figure 2. We can find two groups. The first one is located around (0° ,90° ) where many globular clusters connect to the Sagittarius Stream. The other one is around the direction (0° ,180° ), where there are dwarf galaxies associated with the VPOS, including the LMC, SMC, Carina, Draco, Fornax, and Ursa Minor (Pawlowski et al. 2012). The orbit norm directions (direction of the angular momentum vector L = (LX, LY, LZ)) of those common stars are also located in a similar region, around ( ϕ , θ ) = ( 202 . ° 9 , − 8 . ° 9 ) $ (\phi,\theta)=(202{{{\overset{\circ}{.}}}}9, -8{{{\overset{\circ}{.}}}}9) $, which indicates an association between the new stream and VPOS.

Checking the phase space distributions of those globular clusters and dwarf galaxies, we find that the Pyxis globular cluster is highly associated with the stream, as is shown in Figure 3. First, it is located on the elongation of the stream. The location of Pyxis is highlighted by the arrow in Figure 1, and by the black-edged blue dot around (l, b)∼(−99° ,7° ) in the left panel in Figure 2. What is more, the stream and Pyxis have similar angular momenta; that is, orbit directions. Second, Pyxis has a similar metallicity of −1.2 (Harris 1996) and CMD distribution. Figure B.1 shows the CMD distribution of the members stars of the stream and the globular cluster Pyxis with black and blue dots, respectively. The members of Pyxis are shifted to the distance of the stream. The extinction of Pyxis from Vasiliev (2019) was adopted. We find that the positions of the red horizontal branch stars are quite consistent. Meanwhile, we do not find any connection with the Cetus-Palca Stream, which is located mainly in the southern hemisphere and tightly associated with the globular cluster NGC 5824 (Chang et al. 2020) that is highlighted with the square in Figure 3.

thumbnail Fig. 3.

Distributions of the common stars, globular clusters, and dwarf galaxies represented by the larger dots and blue and yellow dots in the phase spaces E versus LX (left) and LZ (right), respectively. The locations of Pyxis and NGC 5824 are highlighted by the larger blue dot and square, respectively.

All the evidence above suggests that the stream and the globular cluster Pyxis have the same origin, a dwarf galaxy with a stellar mass of 2.0 × 107 M⊙. The new stream and the globular cluster Pyxis bear a close resemblance to the Sagittarius system or the ω-Centauri system, composed of a stripped stream, and at least one globular cluster and the progenitor dwarf galaxy. What is different is that the new stream has a much larger pericenter distance than Sagittarius and the ω-Centauri system. That means that the tidal effect from the Milky Way is much smaller than that on Sagittarius and the ω-Centauri system. We note that Pyxis is a quite special globular cluster with a very large half-light radius, rh = 17.7 pc (Fritz et al. 2017), which is larger than that of almost all currently discovered globular clusters in the Milky Way and close to the lower limit of the dwarf galaxies (Drlica-Wagner et al. 2020). The large pericenter distance means that the globular cluster Pyxis survived the tidal effect of the Milky Way during the disruption of the progenitor dwarf galaxy.

According to the results from Hoyer et al. (2021) based on the analysis of 601 galaxies in the local volume, the occupation of the nuclear star cluster in the galaxies with stellar masses of < 109.5 M⊙ can reach up to 40%. More evidence is necessary from further studies on the relation between the globular cluster Pyxis and the progenitor dwarf galaxy to find out, for example, whether Pyxis is the nuclear star cluster or a satellite globular cluster of the progenitor dwarf galaxy, or whether Pyxis is the remnant of the core of the dwarf galaxy, whose outskirts have been completely stripped. In any case, it is possible that the progenitor dwarf galaxy of the stream has been almost fully disrupted like the ω-Centauri system (Ibata et al. 2019).

The discovery of this new stream suggests again that many globular clusters, especially relatively metal rich ones, were not formed in the Milky Way but in merged dwarf galaxies. Moreover, some of those globular clusters are the nuclear star clusters of the stripped galaxies (Zinn 1993; Muratov & Gnedin 2010; Renaud et al. 2017; Drlica-Wagner et al. 2020). Meanwhile the discovery of the new stream also indicates that many dwarf galaxies have been stripped during the evolution of the Milky Way, even massive ones. This at least partly explains the ‘missing satellites’ problem.

4. Summary

Focusing on distant volumes, we removed the majority of nearby stars with a parallax provided by Gaia DR3. Slicing the proper motions in both directions along α and δ, we found a 110 degrees long stellar stream with 0.5 < μα* < 1.5 and −0.5 < μδ < 0.5 mas yr−1, which is around ∼27.42 kpc from the Sun. Through number fitting along the latitude ϕ2 perpendicular to the elongation of the stream with a Gaussian profile, we find the half width is around 1.23 kpc (1σ in Gaussian). The tangential velocity dispersion perpendicular to the stream is around 22.4 km s−1. The larger width and velocity dispersion indicate an origin from a dwarf galaxy. With the help of LAMOST and DESI, we obtained full information on 18 stars that have high probabilities of being stream members. The metallicity [Fe/H] = −1.3 indicates that the stellar mass of its progenitor is around 2.0 × 107 M⊙, which is much larger than the majority of dwarf galaxies in the Milky Way, next to the Magellanic system and the Sagittarius and Fornax dwarf galaxies. What is more, the orbits of those stars indicate that this stream is associated with the VPOS. More importantly, we find that the globular cluster Pyxis is tightly associated with the new stream. As with the ω-Centauri system, the progenitor dwarf galaxy should have been completely disrupted. It is not clear if Pyxis is the nuclear star cluster or a satellite globular cluster of the progenitor dwarf galaxy. This discovery proves that many of the globular clusters in the Milky Way were formed from the merged dwarf galaxies. This newly discovered stream also indicates that the missed satellites, even massive ones, may have been disrupted during the evolution. Tidal disruption is one of the solutions to the ‘missing satellites’ problem. There should be many diffuse low-surface-density streams in the halo.

2

The longitude range is directly relative to the selection of the two points.

Acknowledgments

We thank the referee for those comments which greatly improved the manuscript. This work is supported by National Key R&D Program of China No. 2024YFA1611902 and the China Manned Space Project. X-X.X. acknowledges the support from CAS Project for Young Scientists in Basic Research Grant No. YSBR-062 and NSFC grants No. 11988101. D.F. acknowledges the support from National Natural Science Foundation of China with Grant No.12273077. J.N. acknowledges the supports by the Beijing Natural Science Foundation (grants No.1232032), by the National Key R&D Program of China (grants No. 2021YFA1600401,2021YFA1600400), by the Chinese National Natural Science Foundation (grants No. 12373019). M.Y. is supported by the National Natural Science Foundation of China (Grant No. 12373048) Y.Y. acknowledges the support from National Natural Science Foundation of China with Grant No.12203064. Data resources are supported by China National Astronomical Data Center (NADC) and Chinese Virtual Observatory (China-VO). This work is supported by Astronomical Big Data Joint Research Center, co-founded by National Astronomical Observatories, Chinese Academy of Sciences and Alibaba Cloud. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. Guoshoujing Telescope (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope LAMOST) is a National Major Scientific Project built by the Chinese Academy of Sciences. Funding for the project has been provided by the National Development and Reform Commission. LAMOST is operated and managed by the National Astronomical Observatories, Chinese Academy of Sciences.

References

  1. Bellazzini, M., Ibata, R. A., Chapman, S. C., et al. 2008, AJ, 136, 1147 [Google Scholar]
  2. Belokurov, V., Evans, N. W., Irwin, M. J., et al. 2007, ApJ, 658, 337 [Google Scholar]
  3. Carballo-Bello, J. A., Sollima, A., Martínez-Delgado, D., et al. 2014, MNRAS, 445, 2971 [Google Scholar]
  4. Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, ArXiv e-prints [arXiv:1612.05560] [Google Scholar]
  5. Chang, J., Yuan, Z., Xue, X.-X., et al. 2020, ApJ, 905, 100 [NASA ADS] [CrossRef] [Google Scholar]
  6. Conroy, C., Bonaca, A., Cargile, P., et al. 2019, ApJ, 883, 107 [NASA ADS] [CrossRef] [Google Scholar]
  7. Dark Energy Survey Collaboration (Abbott, T., et al.) 2016, MNRAS, 460, 1270 [Google Scholar]
  8. Dinescu, D. I., Majewski, S. R., Girard, T. M., & Cudworth, K. M. 2000, AJ, 120, 1892 [Google Scholar]
  9. Dodd, E., Callingham, T. M., Helmi, A., et al. 2023, A&A, 670, L2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  10. Drlica-Wagner, A., Bechtol, K., Mau, S., et al. 2020, ApJ, 893, 47 [CrossRef] [Google Scholar]
  11. Erb, D. K., Shapley, A. E., Pettini, M., et al. 2006, ApJ, 644, 813 [NASA ADS] [CrossRef] [Google Scholar]
  12. Fritz, T. K., Linden, S. T., Zivick, P., et al. 2017, ApJ, 840, 30 [Google Scholar]
  13. Gialluca, M. T., Naidu, R. P., & Bonaca, A. 2021, ApJ, 911, L32 [NASA ADS] [CrossRef] [Google Scholar]
  14. Green, G. 2018, The Journal of Open Source Software, 3, 695 [Google Scholar]
  15. Grillmair, C. J. 2006, ApJ, 645, L37 [Google Scholar]
  16. Grillmair, C. J. 2009, ApJ, 693, 1118 [NASA ADS] [CrossRef] [Google Scholar]
  17. Grillmair, C. J. 2014, ApJ, 790, L10 [Google Scholar]
  18. Grillmair, C. J. 2022, ApJ, 929, 89 [NASA ADS] [CrossRef] [Google Scholar]
  19. Grillmair, C. J., & Dionatos, O. 2006, ApJ, 643, L17 [Google Scholar]
  20. Grillmair, C. J., & Johnson, R. 2006, ApJ, 639, L17 [NASA ADS] [CrossRef] [Google Scholar]
  21. Grillmair, C. J., Cutri, R., Masci, F. J., et al. 2013, ApJ, 769, L23 [Google Scholar]
  22. Harris, W. E. 1996, AJ, 112, 1487 [Google Scholar]
  23. Helmi, A. 2020, ARA&A, 58, 205 [Google Scholar]
  24. Helmi, A., Babusiaux, C., Koppelman, H. H., et al. 2018, Nature, 563, 85 [Google Scholar]
  25. Henry, A., Scarlata, C., Domínguez, A., et al. 2013, ApJ, 776, L27 [NASA ADS] [CrossRef] [Google Scholar]
  26. Hoyer, N., Neumayer, N., Georgiev, I. Y., Seth, A. C., & Greene, J. E. 2021, MNRAS, 507, 3246 [NASA ADS] [CrossRef] [Google Scholar]
  27. Ibata, R. A., Gilmore, G., & Irwin, M. J. 1994, Nature, 370, 194 [Google Scholar]
  28. Ibata, R., Irwin, M., Lewis, G. F., & Stolte, A. 2001, ApJ, 547, L133 [Google Scholar]
  29. Ibata, R. A., Bellazzini, M., Malhan, K., Martin, N., & Bianchini, P. 2019, Nature Astronomy, 3, 667 [Google Scholar]
  30. Ibata, R., Malhan, K., Tenachi, W., et al. 2024, ApJ, 967, 89 [NASA ADS] [CrossRef] [Google Scholar]
  31. Johnston, K. V., Bullock, J. S., Sharma, S., et al. 2008, ApJ, 689, 936 [Google Scholar]
  32. Kirby, E. N., Cohen, J. G., Guhathakurta, P., et al. 2013, ApJ, 779, 102 [Google Scholar]
  33. Klypin, A., Gottlöber, S., Kravtsov, A. V., & Khokhlov, A. M. 1999, ApJ, 516, 530 [NASA ADS] [CrossRef] [Google Scholar]
  34. Koposov, S., Belokurov, V., Evans, N. W., et al. 2008, ApJ, 686, 279 [NASA ADS] [CrossRef] [Google Scholar]
  35. Koposov, S. E., Erkal, D., Li, T. S., et al. 2023, MNRAS, 521, 4936 [NASA ADS] [CrossRef] [Google Scholar]
  36. Koppelman, H., Helmi, A., & Veljanoski, J. 2018, ApJ, 860, L11 [NASA ADS] [CrossRef] [Google Scholar]
  37. Li, T. S., Koposov, S. E., Zucker, D. B., et al. 2019, MNRAS, 490, 3508 [NASA ADS] [CrossRef] [Google Scholar]
  38. Liu, C., Fu, J., Shi, J., et al. 2020, Research in Astronomy and Astrophysics, submitted [arXiv:2005.07210] [Google Scholar]
  39. Majewski, S. R., Skrutskie, M. F., Weinberg, M. D., & Ostheimer, J. C. 2003, ApJ, 599, 1082 [NASA ADS] [CrossRef] [Google Scholar]
  40. Malhan, K., & Ibata, R. A. 2018, MNRAS, 477, 4063 [Google Scholar]
  41. Malhan, K., & Rix, H.-W. 2024, ApJ, 964, 104 [NASA ADS] [CrossRef] [Google Scholar]
  42. Malhan, K., Ibata, R. A., Carlberg, R. G., et al. 2019, ApJ, 886, L7 [NASA ADS] [CrossRef] [Google Scholar]
  43. Malhan, K., Yuan, Z., Ibata, R. A., et al. 2021, ApJ, 920, 51 [NASA ADS] [CrossRef] [Google Scholar]
  44. Martínez-Delgado, D., Zinn, R., Carrera, R., & Gallart, C. 2002, ApJ, 573, L19 [CrossRef] [Google Scholar]
  45. Massari, D., Koppelman, H. H., & Helmi, A. 2019, A&A, 630, L4 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  46. Mateu, C., Read, J. I., & Kawata, D. 2018, MNRAS, 474, 4112 [Google Scholar]
  47. Muratov, A. L., & Gnedin, O. Y. 2010, ApJ, 718, 1266 [Google Scholar]
  48. Naidu, R. P., Conroy, C., Bonaca, A., et al. 2020, ApJ, 901, 48 [Google Scholar]
  49. Newberg, H. J., Yanny, B., & Willett, B. A. 2009, ApJ, 700, L61 [NASA ADS] [CrossRef] [Google Scholar]
  50. Nie, J., Tian, H., Li, J., et al. 2022, ApJ, 930, 23 [NASA ADS] [CrossRef] [Google Scholar]
  51. Pawlowski, M. S., Pflamm-Altenburg, J., & Kroupa, P. 2012, MNRAS, 423, 1109 [NASA ADS] [CrossRef] [Google Scholar]
  52. Planck Collaboration Int. XXIX. 2016, A&A, 586, A132 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  53. Price-Whelan, A. M. 2017, The Journal of Open Source Software, 2, 388 [Google Scholar]
  54. Renaud, F., Agertz, O., & Gieles, M. 2017, MNRAS, 465, 3622 [NASA ADS] [CrossRef] [Google Scholar]
  55. Riley, A. H., & Strigari, L. E. 2020, MNRAS, 494, 983 [NASA ADS] [CrossRef] [Google Scholar]
  56. Rockosi, C. M., Odenkirchen, M., Grebel, E. K., et al. 2002, AJ, 124, 349 [NASA ADS] [CrossRef] [Google Scholar]
  57. Sales, L. V., Helmi, A., Starkenburg, E., et al. 2008, MNRAS, 389, 1391 [Google Scholar]
  58. Shipp, N., Drlica-Wagner, A., Balbinot, E., et al. 2018, ApJ, 862, 114 [Google Scholar]
  59. Thomas, G. F., & Battaglia, G. 2022, A&A, 660, A29 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  60. Tian, H., Liu, C., Luo, C., Xue, X.-X., & Yang, Y. 2024, ApJ, 965, 10 [Google Scholar]
  61. Vasiliev, E. 2019, MNRAS, 482, 1525 [Google Scholar]
  62. Wang, S., & Chen, X. 2019, ApJ, 877, 116 [Google Scholar]
  63. Wilson, J. C., Hearty, F. R., Skrutskie, M. F., et al. 2019, PASP, 131,055001 [NASA ADS] [CrossRef] [Google Scholar]
  64. Yang, C., Xue, X.-X., Li, J., et al. 2019, ApJ, 880, 65 [NASA ADS] [CrossRef] [Google Scholar]
  65. York, D. G., Adelman, J., Anderson, J. E., Jr, et al. 2000, AJ, 120, 1579 [Google Scholar]
  66. Yuan, Z., Chang, J., Beers, T. C., & Huang, Y. 2020, ApJ, 898, L37 [Google Scholar]
  67. Yuan, Z., Malhan, K., Sestito, F., et al. 2022, ApJ, 930, 103 [NASA ADS] [CrossRef] [Google Scholar]
  68. Zahid, H. J., Geller, M. J., Kewley, L. J., et al. 2013, ApJ, 771, L19 [NASA ADS] [CrossRef] [Google Scholar]
  69. Zinn, R. 1993, in The Globular Cluster-Galaxy Connection, eds. G. H. Smith, & J. P. Brodie, ASP Conf. Ser., 48, 38 [NASA ADS] [Google Scholar]

Appendix A: space distribution

The coordinates rotation is done with the package gala. The two coordinates on the stream (α1, δ1) = (169.6, −16.9) and (α2, δ2) = (216.9, 11.5) are adopted. The left panel in Figure A.1 shows the distribution of the stars in the new coordinate frame. The shadow region represents the selection for the member stars. The right panel represents the number distribution along the latitude ϕ2 with −45° < ϕ1 < 65°. The dashed line represents the fitting results with the latitude dispersion of σϕ2 = 2° .57 for a Gaussian distribution y = A ∗ G a u s s i a n ( ϕ 2 ¯ , σ ϕ 2 ) + H $ y=A*Gaussian(\bar{\phi_2},\sigma_{\phi_2})+H $. The background H = 12.54.

thumbnail Fig. A.1.

The sky distribution of the stars in the new coordinates is showed in the left panel. The shadow region represents the coverage of the new stream with −45° < ϕ1 < 65° and |ϕ2|< 5°. The stars with arrows represent the stars with RV from LAMOST (red) and DESI (magenta). The arrows represent the tangential velocities with Solar motion corrected. The right panel shows the number distribution of the stars along the latitude ϕ2 with longitude −45° < ϕ1 < 65°. The dashed line represents the fitting results with a Gaussian distribution.

Appendix B: Distance

Among the selected member candidate stars, there are not classical distance tracers, such as the RR Lyrae stars or blue horizontal stars. The distance is constrained with the isochrone fitting in the color-magnitude diagram distribution of the member candidates, as showed in Figure B.1. Concerning the potential distance gradient, we divide the member candidates into 5 subsamples according to the longitude ϕ1 with binsize of 22°. The dashed line in each panel represents the magnitude in G−band of 17.6, approximately the red horizontal branch stars with distance modulus of 17.19. The member stars of the globular cluster Pyxis selected from Gaia DR3 according to the position and proper motion are also represented by the blue dots and shifted to the similar distance with the stream.

thumbnail Fig. B.1.

The distribution of the member stars in the color magnitude diagram, BP − RP versus G within different longitude ϕ1 ranges. The common stars with LAMOST and DESI are marked with red and magenta dots, respectively. The horizontal dashed line in each panel represents G = 17.6 for testing the distance gradient.

Appendix C: Velocity correction

The contribution of the Solar motion to the proper motions of each stars is different because of the different distance and sky position. With distance of each star, this contribution from the Solar motion can be corrected with gala. The bottom panel in Figure C.1 shows the tangential velocities versus the longitude ϕ1 with the Solar motion corrected. The green symbols represent the average values and the dispersion with different longitude ϕ1.

thumbnail Fig. C.1.

Top: distribution of the RV versus the longtitude ϕ1 of all those common stars from LAMOST and DESI, which are represented by the red and magenta squares, respectively. Bottom: distributions of the tangential velocities VT versus the longtitude ϕ1 of all the member candidate stars with magnitude G < 18. The green lines and the errorbars represent the mean values and the dispersions of the two tangeltial velocities along the two directions ϕ1 and ϕ2 in each subsample with step of Δϕ1 = 22°. The shadow regions represent the edges of the tangential velocities caused by the proper motion selection.

All Figures

thumbnail Fig. 1.

Density distribution of the selected stars over the northern hemisphere. The orbits of four streams are represented by the solid lines, which are provided by Mateu et al. (2018) and Chang et al. (2020). The globular cluster Pyxis is marked with red arrow with ( l , b ) = ( 261 . ° 32 , 7 . ° 00 ) $ (l,b)=(261{{{\overset{\circ}{.}}}}32, 7{{{\overset{\circ}{.}}}}00) $.
In the text
thumbnail Fig. 2.

Left: sky projection of the common stars, globular clusters, and dwarf galaxies represented by squares, blue dots, and yellow dots, respectively. The globular cluster Pyxis and LMC/SMC are highlighted with a larger blue dot and yellow pentagons. All globular clusters and dwarf galaxies with distances larger than 20 kpc are highlighted with a solid black edge. The integrated orbits of those stars with full 6D information are represented by the gray lines. Right: Direction distribution of the orbit normals of those common stars, distant globular clusters and dwarf galaxies with full 6D information. The symbols are the same as in the left panel. The shadow region represents the direction of the normal of the VPOS with a longitude between 150° and 210° and a latitude between −30° and 30°.
In the text
thumbnail Fig. 3.

Distributions of the common stars, globular clusters, and dwarf galaxies represented by the larger dots and blue and yellow dots in the phase spaces E versus LX (left) and LZ (right), respectively. The locations of Pyxis and NGC 5824 are highlighted by the larger blue dot and square, respectively.
In the text
thumbnail Fig. A.1.

The sky distribution of the stars in the new coordinates is showed in the left panel. The shadow region represents the coverage of the new stream with −45° < ϕ1 < 65° and |ϕ2|< 5°. The stars with arrows represent the stars with RV from LAMOST (red) and DESI (magenta). The arrows represent the tangential velocities with Solar motion corrected. The right panel shows the number distribution of the stars along the latitude ϕ2 with longitude −45° < ϕ1 < 65°. The dashed line represents the fitting results with a Gaussian distribution.
In the text
thumbnail Fig. B.1.

The distribution of the member stars in the color magnitude diagram, BP − RP versus G within different longitude ϕ1 ranges. The common stars with LAMOST and DESI are marked with red and magenta dots, respectively. The horizontal dashed line in each panel represents G = 17.6 for testing the distance gradient.
In the text
thumbnail Fig. C.1.

Top: distribution of the RV versus the longtitude ϕ1 of all those common stars from LAMOST and DESI, which are represented by the red and magenta squares, respectively. Bottom: distributions of the tangential velocities VT versus the longtitude ϕ1 of all the member candidate stars with magnitude G < 18. The green lines and the errorbars represent the mean values and the dispersions of the two tangeltial velocities along the two directions ϕ1 and ϕ2 in each subsample with step of Δϕ1 = 22°. The shadow regions represent the edges of the tangential velocities caused by the proper motion selection.
In the text

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