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Since all sources but one (J103853.29+392151.12) show only narrow emission lines, we used the stellar velocity dispersion (σ∗) found through the fitting of the stellar kinematic component to estimate the BH mass. To do this, we used the relation from McConnell & Ma (2013): log10 \u0010 MBH M⊙ \u0011 =(8.32±0.05)+(5.64±0.32) log 10 \u0010 σ∗ 200 km s−1 \u0011 . (1) Using these mass estimates, we derived the corresponding Eddington (1916) luminosity (LEdd) of each AGN in the 23 pairs with an optical spectrum. We then proceeded to estimate their bolometric luminosity (Lbol), which is needed to compute the Ed- dington ratio (λEdd, defined asL bol/LEdd). We assumed the bolo- metric correction factor from Duras et al.","citing_arxiv_id":"2604.14900"},{"n":1,"role":"method","polarity":"use_method","paper_title":"Galactic-scale evolution of classical and complex radio galaxies. Impact of ambient morphology and jet geometry","primary_cat":"astro-ph.GA","context_text":"(1) x′ ≡xcosΘ−ysinΘ(2) y′ ≡xsinΘ +ycosΘ(3) where,a,b, andcrepresent the effective core radii of the ellip- soidal medium, with respective values of 1 4, 2 3, and 1 3 ofL 0, and β=0.5 (Rossi et al. 2017). This configuration produces a triaxial environment of hot gas (∼1.9 kev), with estimated column den- sities, R n(partiles/cc)·dl(integration length)≡[2.8,1.5,1.1]× 1022 cm−2 along the major, intermediate, and minor axes, respec- tively. The parameterΘ(the rotation angle measured from they- axis) controls the orientation of the host galaxy in thex-yplane, with thez-axis serving as the axis of rotation, as illustrated in Fig. 5. In line with the focus on investigating how the ambient medium influences jet evolution with varying propagation direc-","citing_arxiv_id":"2604.05471"},{"n":1,"role":"method","polarity":"use_method","paper_title":"Tracing nitrogen enrichment across cosmic time with JWST","primary_cat":"astro-ph.GA","context_text":"with CLOUDY from single-cloud models; this is indeed an ex- treme simplification but this is just to show what would hap- pen in presence of very high densities to this diagnostic. For the models, we consider the star-forming models described in Ceci et al. (2025), which span a wide range of densities (log(ne)=[0, 7]) and ionisation parameters (log U=[-4, -1]). These models are computed with CLOUDY version 23.01 (Gunasekera et al. 2023), adopting as ionising continua BPASS stellar population models with binaries (Stanway & Eldridge 2018) and a Kroupa (2002) IMF with an upper mass cutoffof 300 M⊙. For this anal- ysis we adopt a fixed stellar age of 106 yr, a stellar metallicity of log(Z⋆)=−1.7, and no depletion onto dust grains.","citing_arxiv_id":"2512.07955"},{"n":1,"role":"dataset","polarity":"use_dataset","paper_title":"APOGEE chemical abundances of stars in the MW satellites Fornax, Sextans, Draco and Carina","primary_cat":"astro-ph.GA","context_text":"Target stars from R20 and this work are marked as blue triangles and red dots, respectively. The N-rich stars are further marked with red circles. The black stars represent GC Fnx 1-5 while the purple star represents GC Fnx 6. (b): Color-magnitude diagram of Fnx stars based onGaia DR3 (grey dots). Table 1.Basic information of our sample stars # APOGEE ID RA DECT e f f logg RVS/N Gmag BP-RP Dwarf Galaxy [deg] [deg] [K] [km s −1] [mag] [mag] 1 2M02403081-3422028 40.12842−34.36745 3626 0.35 81 83 17.61 1.77 Fnx 2 2M02372118-3437451 39.33825−34.62923 3845 0.74 63 112 17.59 1.93 Fnx 3 2M02392578-3442220 39.85744−34.70617 3586 0.27 59 130 17.40 2.19 Fnx 4 2M02402354-3415204 40.09813−34.25565 3552 0.24 36 96 17.70 2.06 Fnx 5 2M02413913-3405505 40.41308−34.09736 3684 0.56 59 79 17.","citing_arxiv_id":"2511.06820"},{"n":1,"role":"method","polarity":"use_method","paper_title":"Seeds to success: growing heavy black holes in dense star clusters","primary_cat":"astro-ph.GA","context_text":"about these mechanisms in Appendix B. 1.3. Cluster relaxation and core-collapse Any gravitationally bound system undergoes dynamical relax- ation driven by the continuous dynamical interactions among its constituents. In a star cluster, this process occurs over a timescale (Spitzer 1969; Binney & Tremaine 2008): trel =4.2 Gyr 15 lnΛ c ! Rh,cl 4 pc ! s Mcl 107 M⊙ ,(1) called half-mass relaxation time, which depends on the cluster mass (Mcl) and the radius within which half of the cluster mass is contained, i.e. the half-mass radius (R h,cl). Relaxation causes light stars to diffuse outward, carrying kinetic energy away from the core. This energy loss makes the core contract, which in turn increases the diffusion, creating a loop that leads the core to col-","citing_arxiv_id":"2511.00200"},{"n":1,"role":"method","polarity":"use_method","paper_title":"Impact of stochastic star-formation histories and dust on selecting quiescent galaxies with JWST photometry","primary_cat":"astro-ph.GA","context_text":"We follow the approach described by Leja et al. (2019a) with prior continuity. The continuity prior constrains the ratio of SFRs between the consecutive time-steps. This approach results in re- duced burstiness, that is, fewer rapid changes in SFR in time. The SFR changes follow the Student-t distribution, which is de- scribed by: PDF(x, ν)= Γ \u0010 ν+1 2 \u0011 √νπΓ \u0010 ν 2 \u0011 1+ (x/σt)2 ν !− ν+1 2 ,(1) whereΓis the Gamma function,νis the degree of freedom, and σt is the scale factor. Since with Student-t distribution, outliers are more likely to occur, it probes a broader range of SFH models than the Gaussian distribution. Using this distribution, we calcu- late the value of SFR as following: SFR(tn)= SFR(tn−1) 10x ,(2) 2 github.com/lisieckik/CIGALE_QGs","citing_arxiv_id":"2509.10117"},{"n":1,"role":"method","polarity":"use_method","paper_title":"The HST-Hyperion Survey: Environmental Imprints on the Stellar-Mass Function at z~2.5","primary_cat":"astro-ph.GA","context_text":"from a LePhare fit. zp and one of zs or zg: In this case, the galaxy has COSMOS2020 photometry and either azg or zs. The spec- z or grism-z also has an associated reliability flag corre- sponding to some confidence in the redshift,qf (described in Section 2). For each MC iteration, a random number,R, is drawn from a uniform distribution on the half-open inter- val [0, 1). If R ≥ qf, then we takezMC ∼ p(z). Otherwise, we take zMC = zs or zMC ∼ g(z), depending on whether the additional redshift is a spec-z or grism-z. zp, zs and zg: Some galaxies in our data have all three types of redshift measurements. In this case, the first step is to compare the confidence levels correspond- ing to the quality flags of the additional redshift mea- surements, which we call qfs and qfg for the spec-z and grism-z, respectively. For clarity, we define the quantity Q ≡ qfmax + qfmin · (1 − qfmax), corresponding to a qfmin-fraction of the way betweenqfmax and 1. That is, if qfmax = 0.95 and qfmin = 0.7, (corresponding to 95% and 70% confidences in the additional redshift measurements) then Q = 0 .95 + 0.7 · (0.05) = 0 .985, or 70% of the way between 0.95 and 1. This way, if the less reliable of the ad- ditional redshifts is selected in a given MC iteration, the remaining interval [qfmax, 1) is weighted according to the confidence associated with that less reliable measurement. With this defined, a random number,R, is drawn from a uniform distribution on the half-open interval[0, 1), and a redshift is assigned depending on which of the additional redshift measurements has a higher confidence. In the case qfmax = qfs > qf g = qfmin (the spec-z is more reliable than the grism-z), a redshift is assigned according to:    R < qf max ⇒ zMC = zs qfmax ≤ R < Q ⇒ zMC ∼ g(z) Q ≤ R < 1 ⇒ zMC ∼ p(z) Conversely, if qfmax = qfg > qf s = qfmin (the grism-z is more reliable than the spec-z), a redshift is assigned ac- cording to:    R < qf max ⇒ zMC ∼ g(z) qfmax ≤ R < Q ⇒ zMC = zs Q ≤ R","citing_arxiv_id":"2509.02714"},{"n":1,"role":"method","polarity":"use_method","paper_title":"Euclid: Early Release Observations. Weak gravitational lensing analysis of Abell 2390","primary_cat":"astro-ph.CO","context_text":"the star-galaxy separation by selecting objects that have a half- light radius larger than 0 .′′09. At the same time we removed faint galaxies with very large (and often non-physical) size es- timates, which can occur for very noisy objects. The magnitude- dependent selection that we adopted for this keeps objects with a half-light radius less than [−0 .′′1875 (IE − 24) + 1 .′′85]. This se- lection excludes all objects with a half-light radius larger than 1 .′′85 at IE = 24, but this limit increases steadily as the galaxies become larger and brighter. Shear weights are defined as in C24. All objects that were flagged or excluded by the selection above were assigned zero weight because they were deemed unsuitable for the WL analysis.","citing_arxiv_id":"2507.07629"}]},"error":null,"updated_at":"2026-05-27T11:27:58.703941+00:00"},"identity_refresh":{"job_type":"identity_refresh","status":"succeeded","result":{"items":[{"title":"Qwen3 Technical Report","outcome":"unchanged","work_id":"25a4e30c-1232-48e7-9925-02fa12ba7c9e","resolver":"local_arxiv","confidence":0.98,"old_work_id":"25a4e30c-1232-48e7-9925-02fa12ba7c9e"}],"counts":{"fixed":0,"merged":0,"unchanged":1,"quarantined":0,"needs_external_resolution":0},"errors":[],"attempted":1},"error":null,"updated_at":"2026-05-27T11:27:58.597131+00:00"},"summary_claims":{"job_type":"summary_claims","status":"succeeded","result":{"title":"\" * write output.state after.block = add.period write newline","claims":[{"claim_text":"NGC 1068 094.B-0321(A) 64.6\" x 63.8\" 5.29 x 5.16 0.9\" 2014-10-06 NGC 253 0102.B-0078(A) 87.4\" x 87.2\" 1.51 x 1.51 0.9\" 2018-11-07 NGC 1320 108.229J.001 63.6\" x 63.8\" 12.51 x 12.55 0.7\" 2022-01-07 13h25m30s 29s 28s 27s 26s 25s □43◦00′45′′ 01′00′′ 15′′ 30′′ RA DEC N 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 1\" 200pc -17 -16.5 -16 -15.5 -15 log(F lux) [erg cm□2s□1] (a) Centaurus A, H α line map. 2h42m42s 41s 40s 39s □0◦00′15′′ 30′′ 45′′ 01′00′′ 15′′ RA DEC N 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17","claim_type":"other","confidence":0.9,"evidence_strength":"citation_context"},{"claim_text":"analysis, as described in the following. Since all sources but one (J103853.29+392151.12) show only narrow emission lines, we used the stellar velocity dispersion (σ∗) found through the fitting of the stellar kinematic component to estimate the BH mass. To do this, we used the relation from McConnell & Ma (2013): log10 \u0010 MBH M⊙ \u0011 =(8.32±0.05)+(5.64±0.32) log 10 \u0010 σ∗ 200 km s−1 \u0011 . (1) Using these mass estimates, we derived the corresponding Eddington (1916) luminosity (LEdd) of each AGN in the 2","claim_type":"method","confidence":0.9,"evidence_strength":"citation_context"},{"claim_text":"about these mechanisms in Appendix B. 1.3. Cluster relaxation and core-collapse Any gravitationally bound system undergoes dynamical relax- ation driven by the continuous dynamical interactions among its constituents. In a star cluster, this process occurs over a timescale (Spitzer 1969; Binney & Tremaine 2008): trel =4.2 Gyr 15 lnΛ c ! 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(J2000) 14 55 08.03 [1] 12 39 46.14 [2] Decl. (J2000) -41 07 13.3 [1] -","claim_type":"background","confidence":0.8,"evidence_strength":"citation_context"}],"why_cited":"Pith tracks \" * write output.state after.block = add.period write newline because it crossed a citation-hub threshold. 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Since all sources but one (J103853.29+392151.12) show only narrow emission lines, we used the stellar velocity dispersion (σ∗) found through the fitting of the stellar kinematic component to estimate the BH mass. To do this, we used the relation from McConnell & Ma (2013): log10 \u0010 MBH M⊙ \u0011 =(8.32±0.05)+(5.64±0.32) log 10 \u0010 σ∗ 200 km s−1 \u0011 . (1) Using these mass estimates, we derived the corresponding Eddington (1916) luminosity (LEdd) of each AGN in the 2","claim_type":"method","confidence":0.9,"evidence_strength":"citation_context"},{"claim_text":"about these mechanisms in Appendix B. 1.3. Cluster relaxation and core-collapse Any gravitationally bound system undergoes dynamical relax- ation driven by the continuous dynamical interactions among its constituents. In a star cluster, this process occurs over a timescale (Spitzer 1969; Binney & Tremaine 2008): trel =4.2 Gyr 15 lnΛ c ! 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The continuity prior constrains the ratio of SFRs between the consecutive time-steps. This approach results in re- duced burstiness, that is, fewer rapid changes in SFR in time. The SFR changes follow the Student-t distribution, which is de- scribed by: PDF(x, ν)= Γ \u0010 ν+1 2 \u0011 √νπΓ \u0010 ν 2 \u0011 1+ (x/σt)2 ν !− ν+1 2 ,(1) whereΓis the Gamma function,νis the degree of freedom, and σt is the scale factor. Since with Student-t ","claim_type":"method","confidence":0.85,"evidence_strength":"citation_context"},{"claim_text":"covering the wavelength of the H 2 line of interest is shown in Figure 1. This data is yet to be corrected for tellurics or blaze; as such it has arbitrary flux units and displays an upward trend with wavelength. Article number, page 3 of 16 A&A proofs:manuscript no. aanda Table 1: Stellar and Disk Parameters for HD 131488 and HD 110058. Parameter HD 131488 References HD 110058 References Spectral Type A1 V [1] A0 V [2] R.A. (J2000) 14 55 08.03 [1] 12 39 46.14 [2] Decl. (J2000) -41 07 13.3 [1] -","claim_type":"background","confidence":0.8,"evidence_strength":"citation_context"}],"why_cited":"Pith tracks \" * write output.state after.block = add.period write newline because it crossed a citation-hub threshold. 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Since all sources but one (J103853.29+392151.12) show only narrow emission lines, we used the stellar velocity dispersion (σ∗) found through the fitting of the stellar kinematic component to estimate the BH mass. To do this, we used the relation from McConnell & Ma (2013): log10 \u0010 MBH M⊙ \u0011 =(8.32±0.05)+(5.64±0.32) log 10 \u0010 σ∗ 200 km s−1 \u0011 . (1) Using these mass estimates, we derived the corresponding Eddington (1916) luminosity (LEdd) of each AGN in the 23 pairs with an optical spectrum. We then proceeded to estimate their bolometric luminosity (Lbol), which is needed to compute the Ed- dington ratio (λEdd, defined asL bol/LEdd). We assumed the bolo- metric correction factor from Duras et al.","citing_arxiv_id":"2604.14900"},{"n":1,"role":"method","polarity":"use_method","paper_title":"Galactic-scale evolution of classical and complex radio galaxies. Impact of ambient morphology and jet geometry","primary_cat":"astro-ph.GA","context_text":"(1) x′ ≡xcosΘ−ysinΘ(2) y′ ≡xsinΘ +ycosΘ(3) where,a,b, andcrepresent the effective core radii of the ellip- soidal medium, with respective values of 1 4, 2 3, and 1 3 ofL 0, and β=0.5 (Rossi et al. 2017). This configuration produces a triaxial environment of hot gas (∼1.9 kev), with estimated column den- sities, R n(partiles/cc)·dl(integration length)≡[2.8,1.5,1.1]× 1022 cm−2 along the major, intermediate, and minor axes, respec- tively. The parameterΘ(the rotation angle measured from they- axis) controls the orientation of the host galaxy in thex-yplane, with thez-axis serving as the axis of rotation, as illustrated in Fig. 5. In line with the focus on investigating how the ambient medium influences jet evolution with varying propagation direc-","citing_arxiv_id":"2604.05471"},{"n":1,"role":"method","polarity":"use_method","paper_title":"Tracing nitrogen enrichment across cosmic time with JWST","primary_cat":"astro-ph.GA","context_text":"with CLOUDY from single-cloud models; this is indeed an ex- treme simplification but this is just to show what would hap- pen in presence of very high densities to this diagnostic. For the models, we consider the star-forming models described in Ceci et al. (2025), which span a wide range of densities (log(ne)=[0, 7]) and ionisation parameters (log U=[-4, -1]). These models are computed with CLOUDY version 23.01 (Gunasekera et al. 2023), adopting as ionising continua BPASS stellar population models with binaries (Stanway & Eldridge 2018) and a Kroupa (2002) IMF with an upper mass cutoffof 300 M⊙. For this anal- ysis we adopt a fixed stellar age of 106 yr, a stellar metallicity of log(Z⋆)=−1.7, and no depletion onto dust grains.","citing_arxiv_id":"2512.07955"},{"n":1,"role":"dataset","polarity":"use_dataset","paper_title":"APOGEE chemical abundances of stars in the MW satellites Fornax, Sextans, Draco and Carina","primary_cat":"astro-ph.GA","context_text":"Target stars from R20 and this work are marked as blue triangles and red dots, respectively. The N-rich stars are further marked with red circles. The black stars represent GC Fnx 1-5 while the purple star represents GC Fnx 6. (b): Color-magnitude diagram of Fnx stars based onGaia DR3 (grey dots). Table 1.Basic information of our sample stars # APOGEE ID RA DECT e f f logg RVS/N Gmag BP-RP Dwarf Galaxy [deg] [deg] [K] [km s −1] [mag] [mag] 1 2M02403081-3422028 40.12842−34.36745 3626 0.35 81 83 17.61 1.77 Fnx 2 2M02372118-3437451 39.33825−34.62923 3845 0.74 63 112 17.59 1.93 Fnx 3 2M02392578-3442220 39.85744−34.70617 3586 0.27 59 130 17.40 2.19 Fnx 4 2M02402354-3415204 40.09813−34.25565 3552 0.24 36 96 17.70 2.06 Fnx 5 2M02413913-3405505 40.41308−34.09736 3684 0.56 59 79 17.","citing_arxiv_id":"2511.06820"},{"n":1,"role":"method","polarity":"use_method","paper_title":"Seeds to success: growing heavy black holes in dense star clusters","primary_cat":"astro-ph.GA","context_text":"about these mechanisms in Appendix B. 1.3. Cluster relaxation and core-collapse Any gravitationally bound system undergoes dynamical relax- ation driven by the continuous dynamical interactions among its constituents. In a star cluster, this process occurs over a timescale (Spitzer 1969; Binney & Tremaine 2008): trel =4.2 Gyr 15 lnΛ c ! Rh,cl 4 pc ! s Mcl 107 M⊙ ,(1) called half-mass relaxation time, which depends on the cluster mass (Mcl) and the radius within which half of the cluster mass is contained, i.e. the half-mass radius (R h,cl). Relaxation causes light stars to diffuse outward, carrying kinetic energy away from the core. This energy loss makes the core contract, which in turn increases the diffusion, creating a loop that leads the core to col-","citing_arxiv_id":"2511.00200"},{"n":1,"role":"method","polarity":"use_method","paper_title":"Impact of stochastic star-formation histories and dust on selecting quiescent galaxies with JWST photometry","primary_cat":"astro-ph.GA","context_text":"We follow the approach described by Leja et al. (2019a) with prior continuity. The continuity prior constrains the ratio of SFRs between the consecutive time-steps. This approach results in re- duced burstiness, that is, fewer rapid changes in SFR in time. The SFR changes follow the Student-t distribution, which is de- scribed by: PDF(x, ν)= Γ \u0010 ν+1 2 \u0011 √νπΓ \u0010 ν 2 \u0011 1+ (x/σt)2 ν !− ν+1 2 ,(1) whereΓis the Gamma function,νis the degree of freedom, and σt is the scale factor. Since with Student-t distribution, outliers are more likely to occur, it probes a broader range of SFH models than the Gaussian distribution. Using this distribution, we calcu- late the value of SFR as following: SFR(tn)= SFR(tn−1) 10x ,(2) 2 github.com/lisieckik/CIGALE_QGs","citing_arxiv_id":"2509.10117"},{"n":1,"role":"method","polarity":"use_method","paper_title":"The HST-Hyperion Survey: Environmental Imprints on the Stellar-Mass Function at z~2.5","primary_cat":"astro-ph.GA","context_text":"from a LePhare fit. zp and one of zs or zg: In this case, the galaxy has COSMOS2020 photometry and either azg or zs. The spec- z or grism-z also has an associated reliability flag corre- sponding to some confidence in the redshift,qf (described in Section 2). For each MC iteration, a random number,R, is drawn from a uniform distribution on the half-open inter- val [0, 1). If R ≥ qf, then we takezMC ∼ p(z). Otherwise, we take zMC = zs or zMC ∼ g(z), depending on whether the additional redshift is a spec-z or grism-z. zp, zs and zg: Some galaxies in our data have all three types of redshift measurements. In this case, the first step is to compare the confidence levels correspond- ing to the quality flags of the additional redshift mea- surements, which we call qfs and qfg for the spec-z and grism-z, respectively. For clarity, we define the quantity Q ≡ qfmax + qfmin · (1 − qfmax), corresponding to a qfmin-fraction of the way betweenqfmax and 1. That is, if qfmax = 0.95 and qfmin = 0.7, (corresponding to 95% and 70% confidences in the additional redshift measurements) then Q = 0 .95 + 0.7 · (0.05) = 0 .985, or 70% of the way between 0.95 and 1. This way, if the less reliable of the ad- ditional redshifts is selected in a given MC iteration, the remaining interval [qfmax, 1) is weighted according to the confidence associated with that less reliable measurement. With this defined, a random number,R, is drawn from a uniform distribution on the half-open interval[0, 1), and a redshift is assigned depending on which of the additional redshift measurements has a higher confidence. In the case qfmax = qfs > qf g = qfmin (the spec-z is more reliable than the grism-z), a redshift is assigned according to:    R < qf max ⇒ zMC = zs qfmax ≤ R < Q ⇒ zMC ∼ g(z) Q ≤ R < 1 ⇒ zMC ∼ p(z) Conversely, if qfmax = qfg > qf s = qfmin (the grism-z is more reliable than the spec-z), a redshift is assigned ac- cording to:    R < qf max ⇒ zMC ∼ g(z) qfmax ≤ R < Q ⇒ zMC = zs Q ≤ R","citing_arxiv_id":"2509.02714"},{"n":1,"role":"method","polarity":"use_method","paper_title":"Euclid: Early Release Observations. Weak gravitational lensing analysis of Abell 2390","primary_cat":"astro-ph.CO","context_text":"the star-galaxy separation by selecting objects that have a half- light radius larger than 0 .′′09. At the same time we removed faint galaxies with very large (and often non-physical) size es- timates, which can occur for very noisy objects. The magnitude- dependent selection that we adopted for this keeps objects with a half-light radius less than [−0 .′′1875 (IE − 24) + 1 .′′85]. This se- lection excludes all objects with a half-light radius larger than 1 .′′85 at IE = 24, but this limit increases steadily as the galaxies become larger and brighter. Shear weights are defined as in C24. All objects that were flagged or excluded by the selection above were assigned zero weight because they were deemed unsuitable for the WL analysis.","citing_arxiv_id":"2507.07629"}]},"authors":[]}}