Population III candidates

This page maintains an up-to-date (as of October 1, 2025) compilation of all reported high-redshift (\(z \gtrsim 3\)) Pop III-hosting galaxy candidates, i.e. galaxies for which the presence of an active Pop III component has been suggested to account for the observed emission – regardless of the average metallicity of the galaxy.

The table below includes key properties of these objects, as reported in their respective discovery papers, including their redshift, magnification, UV magnitude (\(M_\mathrm{UV}\)), UV \(\beta\)-slope, stellar mass (the total stellar mass, \(M_\star\), and mass of the proposed Pop III component, \(M_\mathrm{III}\)), star formation rate (SFR), line flux, equivalent width (EW) and full width half maximum (FWHM) for a selection of emission lines of interest (Ly\(\alpha\), H\(\alpha\), H\(\beta\), HeII1640, HeII4686 and [OIII]5007), [OIII]/H\(\beta\) ratio and metallicity, both in terms of O/H ratio and solar metallicity (Z\(_\odot\)).

The table is dynamically generated in the code block below, and it can be automatically exported to various formats for further use in analysis or publications.

from IPython.display import Markdown
from tabulate import tabulate
from astropy.table import Table
from types import MethodType
from format_multiple_errors import format_multiple_errors
from numbers import Real
import numpy as np
import math


def format_cell(x, 
                exponential=False, 
                digits=2):
    """
    Render a single table cell in latex depending on the type of x:
      - scalar -> single value
      - 1-tuple/list/np.array (value,) -> treat like scalar
      - 2-tuple/list/np.array (value, err) -> value ± err
      - 3-tuple/list/np.array (value, err_minus, err_plus) -> value_{-err_minus}^{+err_plus}
    Formatted as exponential if exponential = True, with the indicated number of digits.
    Format overrides may also be specified in a dictionary at the end of the tuple.
    Non-numerical values are returned as string unchanged, if allowed.
    """
    # TODO: improve automatic choice of exponential and digits value when unspecified
    # Missing value
    if x is None:
        return "—"

    list_formats = (list, tuple, np.ndarray)
    numeric_formats = (Real, np.floating, np.integer)

    # Scalar number
    fmt = f".{digits}{'e' if exponential else 'f'}"  # Format
    if isinstance(x, np.ndarray) and x.ndim == 0:  # Regularize potential ndarray 0D (e.g. np.array(value)) to python scalars
        x = x.item()
    if isinstance(x, numeric_formats):  # Plain scalar value
        return fr"${x:{fmt}}$"
    if isinstance(x, list_formats) and len(x) == 1:  # Or 1-tuple -> treat like scalar
        value = x[0]
        if isinstance(value, numeric_formats):
            return fr"${value:{fmt}}$"

    # Significant figures given digits
    def sigfig(digits, value):
        e = 0 if value == 0 else int(math.floor(math.log10(abs(value))))
        return max(1, digits + e + 1) if not exponential else digits + 1

    # 2-tuple symmetric uncertainty
    if isinstance(x, list_formats) and len(x) == 2 and all(isinstance(v, numeric_formats) for v in x):
        value, err = x
        return rf"${format_multiple_errors(value, err, exponential=exponential, significant_figures=sigfig(digits, value), length_control='central', latex=True)}$"

    # 3-tuple asymmetric uncertainty
    if isinstance(x, list_formats) and len(x) == 3 and all(isinstance(v, numeric_formats) for v in x):
        value, err_lower, err_upper, = x
        return rf"${format_multiple_errors(value, (err_lower, err_upper), exponential=exponential, significant_figures=sigfig(digits, value), length_control='central', latex=True)}$"

    # Special case: entry includes explicit format overrides as a dictionary in the last element of the tuple
    if isinstance(x, list_formats) and isinstance(x[-1], dict):
        *values, fmt_overrides = x
        note = fmt_overrides.pop("note", "")  # Return value associated to the key and remove entry from dictionary (otherwise format_cell() produces an error)
        fmt_merged = {
            "exponential": exponential, 
            "digits": digits, 
            **fmt_overrides
            }  # Shallow merge: if duplicate key in dictionary, take the last one, effectively overriding the specified format parameters
        values_unpacked = values[0] if len(values) == 1 else tuple(values)
        return format_cell(values_unpacked, **fmt_merged) + note

    # Fallback: try to convert to string, or raise exception
    try:
        return str(x)
    except:
        raise ValueError(f"Unrecognized cell format for entry {x}")


def table_to_markdown(tbl, 
                      exponential=False,
                      digits=2,
                      col_fmt_overrides=None,
                      headers=None,
                      **kwargs):
    """
    Convert an Astropy Table into a Markdown table, formatting every cell through the format_cell() function.
    Formatting instructions passed to format_cell() can be overridden for specific columns through the col_fmt_overrides field
    """

    default_fmt = {
        "exponential": exponential, 
        "digits": digits
        }  

    rows = []
    for r in tbl:
        row = []
        for c in tbl.colnames:
            if col_fmt_overrides is None:
                fmt = default_fmt  # Default format
            else:
                fmt = {**default_fmt, **col_fmt_overrides.get(c, {})}  # Shallow merge: if duplicate key, take the last one, overriding the specified format parameters for current column
            row.append(format_cell(r[c], **fmt))
        rows.append(row)

    if headers is None:
        headers = tbl.colnames

    md = tabulate(
        rows,
        headers,
        **kwargs
    )
    return md

# ---------------- Example usage ----------------

# Map column name --> (header, units); TODO: units using astropy.units and converting when formatting header
colmap = {
    "ID":            ("Name",               None),
    "redshift":      ("Redshift",           None),
    "magnification": ("Lensed",             None),
    "MUV":           (r"$M_{\rm UV}$",      None),
    "beta":          (r"$\beta$-slope",     None),
    "Mstar":         (r"$M_\star$",         r"M$_\odot$"),
    "MIII":          (r"$M_\mathrm{III}$",  r"M$_\odot$"),
    "SFR":           ("SFR",                r"M$_\odot$yr$^{-1}$"),
    "Lya_flux":      (r"Ly$\alpha$ flux",   r"erg s$^{-1}$ cm$^{-2}$"),
    "Lya_EW":        (r"Ly$\alpha$ EW",     "Å"),
    "Lya_FWHM":      (r"Ly$\alpha$ FWHM",   r"km s$^{-1}$"),
    "Ha_flux":       (r"H$\alpha$ flux",    r"erg s$^{-1}$ cm$^{-2}$"),
    "Ha_EW":         (r"H$\alpha$ EW",      "Å"),
    "Ha_FWHM":       (r"H$\alpha$ FWHM",    r"km s$^{-1}$"),
    "Hb_flux":       (r"H$\beta$ flux",     r"erg s$^{-1}$ cm$^{-2}$"),
    "Hb_EW":         (r"H$\beta$ EW",       "Å"),
    "Hb_FWHM":       (r"H$\beta$ FWHM",     r"km s$^{-1}$"),
    "HeII1640_flux": ("HeII1640 flux",      r"erg s$^{-1}$ cm$^{-2}$"),
    "HeII1640_EW":   ("HeII1640 EW",        "Å"),
    "HeII1640_FWHM": ("HeII1640 FWHM",      r"km s$^{-1}$"),
    "HeII4686_flux": ("HeII4686 flux",      r"erg s$^{-1}$ cm$^{-2}$"),
    "HeII4686_EW":   ("HeII4686 EW",        "Å"),
    "HeII4686_FWMH": ("HeII4686 FWHM",      r"km s$^{-1}$"),
    "OIII5007_flux": ("[OIII]5007 flux",    r"erg s$^{-1}$ cm$^{-2}$"),
    "OIII5007_EW":   ("[OIII]5007 EW",      "Å"),
    "OIII5007_FWHM": ("[OIII]5007 FWHM",    r"km s$^{-1}$"),
    "OIIItoHb":      (r"[OIII]/H$\beta$",   None),
    "OtoH":          ("12 + log(O/H)",      None),
    "metallicity":   ("Metallicity",        r"Z$_\odot$"),
    "reference":     ("Reference",          None),
}
names = tuple(colmap.keys())
headers = tuple(
    (fr"{label}<br>[{unit}]" if unit else f"{label}<br>&nbsp;")
    for (label, unit) in colmap.values()
)

# Setup table
table = Table( 
    names=names,
    dtype=("object",)*len(names),
    masked=True
)

# Minor patch of astropy table add_row method, so that missing values are set to None by default instead of 0
defaults = {c: None for c in table.colnames}
def add_row_with_defaults(self, row=None, *args, **kwargs):
    if isinstance(row, dict):
        row = {**defaults, **row}
    return Table.add_row(self, row, *args, **kwargs)
table.add_row = MethodType(add_row_with_defaults, table)

# Column format overrides
col_fmt_overrides = {
    "Mstar": {"exponential": True},
    "MIII": {"exponential": True},
    "Lya_flux": {"exponential": True}, 
    "Ha_flux": {"exponential": True}, 
    "Hb_flux": {"exponential": True}, 
    "HeII1640_flux": {"exponential": True},
    "HeII4686_flux": {"exponential": True},
    "OIII5007_flux": {"exponential": True},
}

# Notes style
def note(text, color="red"):
    return rf"$^{{\textcolor{{{color}}}{{({text})}}}}$"

# Fill table
table.add_row(dict(
    ID="GNHeII J1236+6215",
    redshift=(2.9803, 0.0010, {"digits": 4}),
    magnification="No",
    MUV=(-22.09, 0.02, {"digits": 2}),
    beta=(-2.18, 0.06, {"digits": 2}),
    Lya_flux=(23.0e-18, 5.4e-18, {"digits": 2}),
    Lya_EW=(19.2),
    Lya_FWHM=(758, 90, {"digits": 0}),  # Note that values for the FWHMs are also given in A in Tab. 4
    Ha_flux=(16.46e-18, 0.32e-18, {"digits": 3}),
    Ha_EW=166.5,
    Ha_FWHM=(268, 41, {"digits": 0}),
    Hb_flux=(5.44e-18, 0.37e-18, {"digits": 2}),
    Hb_EW=(26.6),
    Hb_FWHM=(320, 137, {"digits": 0}),
    HeII1640_flux=(8.8e-18, 1.8e-18),
    HeII1640_EW=8.3,
    HeII1640_FWHM=(573, 191, {"digits": 0}),
    Mstar=(7.8e8, 3.1e8),
    SFR=(12.2, 2.0, {"note": note("a")}),  # From SED, i.e. the value reported in the abstract
    OIII5007_flux=(59.6e-18, 2.2e-18, {"digits": 2}),
    OIII5007_EW=248.8,
    OIIItoHb=(5.45, 0.32, {"digits": 2}),  # They also give HeII/Hbeta = 1.96 \pm 0.30, and HeII/Halpha = 0.69, 0.10, reported to closely match with the candidate from Wang+24
    OtoH=(7.85, 0.22, {"digits": 2}),
    metallicity=(0.003, 0.002, {"digits": 3}),
    reference="@mondal2025"
))
table.add_row(dict(
    ID="MPG-CR3",
    redshift=(3.193, 0.016, {"digits": 3}),
    magnification="No",
    Lya_flux=(5.8e-17, 0.7e-17),
    Lya_EW=(822, 101, {"digits": 0}),
    Ha_flux=(4.2e-18, 0.6e-18, {"note": note("b")}),
    Ha_EW=(2814, 327, {"digits": 0}),
    Hb_flux=(6.3e-19, 0.7e-19),
    HeII1640_flux=(None, {"note": note("c")}),
    MIII=6.1e5,
    OIII5007_flux=r"$< 5.6 \times 10^{-19}$",  # At 2sigma
    OtoH=r"$< 6.52$",
    metallicity=r"$< 8 \times 10^{-3}$",
    reference="@cai2025"
))
table.add_row(dict(
    ID="AMORE6",
    redshift=(5.7253, 0.00005, {"digits": 4}),
    magnification=("Yes", {"note": note("d")}),  # $\mu = 39.32_{-3.48}^{+3.73}$ for AMORE6-A, vs $\mu = 77.69_{-5.92}^{+8.37}$ for AMORE6-B
    MUV=(-14.52, 0.08, 0.07, {"digits": 2, "note": note("e")}),
    beta=(-2.77, 0.09, 0.07, {"digits": 2}),
    Lya_flux= (4.95e-19, 0.92e-19, {"digits": 2}),  # From Lyalpha-to-Hbeta ratio = 10.01 \pm 1.4, propagating uncertainties
    Hb_flux=(0.49e-19, 0.06e-19),
    Hb_EW=(1594.7, 206.9),
    Mstar=(4.37e5, 0.73e5, 2.24e5, {"digits": 2}),
    SFR=(0.35, 0.06, {"digits": 2, "note": note("f")}),  # From Hbeta, converting from log to linear
    OIII5007_flux=r"$< 1.1 \times 10^{-20}$",   # Upper limits at 2sigma
    OtoH=r"$< 5.78$",
    metallicity=r"$< 0.0012$", 
    reference="@morishita2025"
))
table.add_row(dict(
    ID="JOF-21739",
    redshift=(6.17, 0.19, 0.06, {"digits": 2}),
    magnification="Yes",  # Value of magnification not indicated
    MUV=(-17.62, 0.15, 0.17, {"digits": 2}),
    beta=(-2.79, 0.05, {"digits": 2}),
    Ha_EW=(3600, 430, {"digits": 0}),
    MIII=r"$\sim 10^5 - 10^6$",
    OIIItoHb=r"$< 0.32$",
    OtoH=r"$< 6.2$",
    metallicity=r"$< 0.003$",
    reference="@fujimoto2025"
))
'''
# Rejected: detected [OIII] in the spectrum
table.add_row(dict(
    ID="GLIMPSE-1604",
    redshift=(6.50, 0.24, 0.03, {"digits": 2}),
    magnification="Yes",  # mu = (2.9, 0.2, 0.1),  
    MUV=(-15.89, 0.14, 0.12, {"digits": 2}),
    beta=(-2.34, 0.36, {"digits": 2}),
    Ha_EW=(2810, 550, {"digits": 0}),
    MIII=r"$\sim 10^5$",
    OIIItoHb=r"$< 0.44$",
    OtoH=r"$< 6.4$",
    metallicity=r"$< 0.005$",
    reference="@fujimoto2025"
))
'''
table.add_row(dict(
    ID="LAP1",
    redshift=(6.639, 0.004, {"digits": 3}),
    magnification="Yes",  # mu_tot(median) = (120, 9), mu_tang(median) = (55, 6, 2), mu_tot > 500 for images A1,A2, mu_tot=98,99 for B1,B2
    MUV=r"$> -11.2$",
    Mstar=r"$\lesssim 10^4$",
    Lya_flux=(369.2e-20, 29.3e-20, {"digits": 3}),
    Lya_EW=r"$> 370$",
    Ha_flux=(69.4e-20, 5.5e-20, {"digits": 2}),
    Ha_EW=r"$> 2020$",
    Hb_flux=(26.3e-20, 2.7e-20, {"digits": 2}),
    Hb_EW=r"$> 420$",
    HeII1640_flux=(79.6e-20, 20.7e-20, {"digits": 2, "note": note("g")}),
    OIII5007_flux=(14.5e-20, 3.4e-20, {"digits": 2}),
    OIII5007_EW=r"$> 246$",
    OIIItoHb=(0.55, 0.14, 0.15, {"digits": 2}),
    OtoH=r"$< 6.3$",
    metallicity=r"$< 0.004$",
    reference="@vanzella2023"
))
table.add_row(dict(
    ID="RX J2129-z8HeII",
    redshift=(8.1623, 0.0007, {"digits": 4}),
    magnification="Yes", # mu = (2.26, 0.14),
    MUV=(-19.58, 0.02, 0.03, {"digits": 2}),
    beta=(-2.53, 0.07, 0.06, {"digits": 2}),
    Mstar=(5.6e7, 0.7e7, 0.8e7),  # Tot. stellar mass of the system LogM*/Msun = 7.75 \pm 0.06 from Tab. 1
    MIII=(7.8e5, 1.4e5),  # Mass of the putative Pop III component estimated from the HeII luminosity
    SFR=(9.56, 1.70, 4.51, {"digits": 2}),
    Hb_flux=(71e-20, 10e-20, {"note": note("h")}),
    Hb_EW=(202, 34, {"digits": 0}),
    HeII1640_flux=(120e-20, 22e-20, {"digits": 2}),
    HeII1640_EW=(21, 4, {"digits": 0}),
    HeII4686_flux=r"$< 1.6 \times 10^{-19}$",  # 2sigma upper limits
    HeII4686_EW=r"$< 49$",
    OIII5007_flux=(390e-20, 10e-20, {"digits": 2}),
    OIII5007_EW=(1015, 83, {"digits": 0}),
    OIIItoHb=(5.5, 0.8),
    OtoH=(7.63, 0.09, 0.14, {"digits": 2}),
    metallicity=r"$\sim 0.1$",  # Log(Zstar/Zsun) ~ -0.9
    reference="@wang2024"
))
table.add_row(dict(
    ID="EXCELS-63107",
    redshift=(8.271, {"digits": 3}),
    magnification="No",
    MUV=(-19.9, 0.1),
    beta=(-3.3, 0.3),
    Mstar=(3.72e8, 3.37e8, 4.05e8, {"digits": 2, "note": note("i")}),  # Assuming extended SF + recent burst model and converting from log to linear --> LogMstar/Msun = 8.57 -1.03 +0.32 to linear, with mass of the burst LogMburst/Msun = 7.35 -1.30 +0.22 (see Sec. 3.3 and Tab. 3)
    SFR=(7.8, 0.6),  # From Hbeta
    Hb_flux=(10.69e-19, 0.84e-19, {"digits": 3}),
    OIII5007_flux=(38.54e-19, 1.20e-19, {"digits": 3}),
    OIIItoHb=(3.61, 0.30, {"digits": 2}),
    OtoH=(6.89, 0.21, 0.26, {"digits": 2, "note": note("j")}),
    metallicity=(0.016, {"digits": 3}),
    reference="@cullen2025"
))
table.add_row(dict(
    ID="GN-z11 HeII clump",
    redshift=(10.6034, 0.0013, {"digits": 4, "note": note("k")}),
    magnification="No",
    MIII=r"$\sim (2 - 2.5) \times 10^5$",
    HeII1640_flux=(1.8e-19, 0.34e-19, {"note": note("l")}),  # Fluxes and EWs from Tab. 2 (HeII clump small aperture), converting log to linear
    HeII1640_EW=(62, 27, 25, {"digits": 0, "note": note("m")}),
    reference="@maiolino2024"
))

# Markdown table
md = table_to_markdown(table, tablefmt="github", headers=headers, exponential=False, digits=1, col_fmt_overrides=col_fmt_overrides)
Markdown(md)

Name	Redshift	Lensed	\(M_{\rm UV}\)	\(\beta\)-slope	\(M_\star\) [M\(_\odot\)]	\(M_\mathrm{III}\) [M\(_\odot\)]	SFR [M\(_\odot\)yr\(^{-1}\)]	Ly\(\alpha\) flux [erg s\(^{-1}\) cm\(^{-2}\)]	Ly\(\alpha\) EW [Å]	Ly\(\alpha\) FWHM [km s\(^{-1}\)]	H\(\alpha\) flux [erg s\(^{-1}\) cm\(^{-2}\)]	H\(\alpha\) EW [Å]	H\(\alpha\) FWHM [km s\(^{-1}\)]	H\(\beta\) flux [erg s\(^{-1}\) cm\(^{-2}\)]	H\(\beta\) EW [Å]	H\(\beta\) FWHM [km s\(^{-1}\)]	HeII1640 flux [erg s\(^{-1}\) cm\(^{-2}\)]	HeII1640 EW [Å]	HeII1640 FWHM [km s\(^{-1}\)]	HeII4686 flux [erg s\(^{-1}\) cm\(^{-2}\)]	HeII4686 EW [Å]	HeII4686 FWHM [km s\(^{-1}\)]	[OIII]5007 flux [erg s\(^{-1}\) cm\(^{-2}\)]	[OIII]5007 EW [Å]	[OIII]5007 FWHM [km s\(^{-1}\)]	[OIII]/H\(\beta\)	12 + log(O/H)	Metallicity [Z\(_\odot\)]	Reference
GNHeII J1236+6215	\(2.9803 \pm 0.0010\)	No	\(-22.09 \pm 0.02\)	\(-2.18 \pm 0.06\)	\((7.8 \pm 3.1) \times 10^{8}\)	—	\(12.2 \pm 2.0\)\(^{\textcolor{red}{(a)}}\)	\((2.30 \pm 0.54) \times 10^{-17}\)	\(19.2\)	\(758 \pm 90\)	\((1.646 \pm 0.032) \times 10^{-17}\)	\(166.5\)	\(268 \pm 41\)	\((5.44 \pm 0.37) \times 10^{-18}\)	\(26.6\)	\(320 \pm 137\)	\((8.8 \pm 1.8) \times 10^{-18}\)	\(8.3\)	\(573 \pm 191\)	—	—	—	\((5.96 \pm 0.22) \times 10^{-17}\)	\(248.8\)	—	\(5.45 \pm 0.32\)	\(7.85 \pm 0.22\)	\(0.003 \pm 0.002\)	Mondal et al. (2025)
MPG-CR3	\(3.193 \pm 0.016\)	No	—	—	—	\(6.1e+05\)	—	\((5.8 \pm 0.7) \times 10^{-17}\)	\(822 \pm 101\)	—	\((4.2 \pm 0.6) \times 10^{-18}\)\(^{\textcolor{red}{(b)}}\)	\(2814 \pm 327\)	—	\((6.3 \pm 0.7) \times 10^{-19}\)	—	—	—\(^{\textcolor{red}{(c)}}\)	—	—	—	—	—	\(< 5.6 \times 10^{-19}\)	—	—	—	\(< 6.52\)	\(< 8 \times 10^{-3}\)	Cai et al. (2025)
AMORE6	\(5.7253 \pm 0.0001\)	Yes\(^{\textcolor{red}{(d)}}\)	\(-14.52 {}^{+0.08}_{-0.07}\)\(^{\textcolor{red}{(e)}}\)	\(-2.77 {}^{+0.09}_{-0.07}\)	\((4.37 {}^{+0.73}_{-2.24}) \times 10^{5}\)	—	\(0.35 \pm 0.06\)\(^{\textcolor{red}{(f)}}\)	\((4.95 \pm 0.92) \times 10^{-19}\)	—	—	—	—	—	\((4.9 \pm 0.6) \times 10^{-20}\)	\(1594.7 \pm 206.9\)	—	—	—	—	—	—	—	\(< 1.1 \times 10^{-20}\)	—	—	—	\(< 5.78\)	\(< 0.0012\)	Morishita et al. (2025)
JOF-21739	\(6.17 {}^{+0.19}_{-0.06}\)	Yes	\(-17.62 {}^{+0.15}_{-0.17}\)	\(-2.79 \pm 0.05\)	—	\(\sim 10^5 - 10^6\)	—	—	—	—	—	\(3600 \pm 430\)	—	—	—	—	—	—	—	—	—	—	—	—	—	\(< 0.32\)	\(< 6.2\)	\(< 0.003\)	Fujimoto et al. (2025)
LAP1	\(6.639 \pm 0.004\)	Yes	\(> -11.2\)	—	\(\lesssim 10^4\)	—	—	\((3.692 \pm 0.293) \times 10^{-18}\)	\(> 370\)	—	\((6.94 \pm 0.55) \times 10^{-19}\)	\(> 2020\)	—	\((2.63 \pm 0.27) \times 10^{-19}\)	\(> 420\)	—	\((7.96 \pm 2.07) \times 10^{-19}\)\(^{\textcolor{red}{(g)}}\)	—	—	—	—	—	\((1.45 \pm 0.34) \times 10^{-19}\)	\(> 246\)	—	\(0.55 {}^{+0.14}_{-0.15}\)	\(< 6.3\)	\(< 0.004\)	Vanzella et al. (2023)
RX J2129-z8HeII	\(8.1623 \pm 0.0007\)	Yes	\(-19.58 {}^{+0.02}_{-0.03}\)	\(-2.53 {}^{+0.07}_{-0.06}\)	\((5.6 {}^{+0.7}_{-0.8}) \times 10^{7}\)	\((7.8 \pm 1.4) \times 10^{5}\)	\(9.56 {}^{+1.70}_{-4.51}\)	—	—	—	—	—	—	\((7.1 \pm 1.0) \times 10^{-19}\)\(^{\textcolor{red}{(h)}}\)	\(202 \pm 34\)	—	\((1.20 \pm 0.22) \times 10^{-18}\)	\(21 \pm 4\)	—	\(< 1.6 \times 10^{-19}\)	\(< 49\)	—	\((3.90 \pm 0.10) \times 10^{-18}\)	\(1015 \pm 83\)	—	\(5.5 \pm 0.8\)	\(7.63 {}^{+0.09}_{-0.14}\)	\(\sim 0.1\)	Wang et al. (2024)
EXCELS-63107	\(8.271\)	No	\(-19.9 \pm 0.1\)	\(-3.3 \pm 0.3\)	\((3.72 {}^{+3.37}_{-4.05}) \times 10^{8}\)\(^{\textcolor{red}{(i)}}\)	—	\(7.8 \pm 0.6\)	—	—	—	—	—	—	\((1.069 \pm 0.084) \times 10^{-18}\)	—	—	—	—	—	—	—	—	\((3.854 \pm 0.120) \times 10^{-18}\)	—	—	\(3.61 \pm 0.30\)	\(6.89 {}^{+0.21}_{-0.26}\)\(^{\textcolor{red}{(j)}}\)	\(0.016\)	Cullen et al. (2025)
GN-z11 HeII clump	\(10.6034 \pm 0.0013\)\(^{\textcolor{red}{(k)}}\)	No	—	—	—	\(\sim (2 - 2.5) \times 10^5\)	—	—	—	—	—	—	—	—	—	—	\((1.8 \pm 0.3) \times 10^{-19}\)\(^{\textcolor{red}{(l)}}\)	\(62 {}^{+27}_{-25}\)\(^{\textcolor{red}{(m)}}\)	—	—	—	—	—	—	—	—	—	—	Maiolino et al. (2024)

\(^{(a)}\) From photometric analysis, averaged over the last 10 Myr; from spectroscopic analysis: SFR\(_\mathrm{UV} = (9.8 \pm 0.1) ~\mathrm{M_\odot yr^{-1}}\), SFR\(_\mathrm{H\beta} = (7.6 \pm 0.4) ~\mathrm{M_\odot yr^{-1}}\), SFR\(_\mathrm{H\alpha} = (7.5 \pm 0.1) ~\mathrm{M_\odot yr^{-1}}\), SFR\(_\mathrm{Pa\beta} = (6.40 \pm 0.03) ~\mathrm{M_\odot yr^{-1}}\).

\(^{(b)}\) Includes a rescaling to account for potential flux losses, as the source lies near the edge of the MSA shutter.

\(^{(c)}\) HeII1640 line coinciding with strong OH skyline for this object.

\(^{(d)}\) Properties for the stacked spectrum of the two images in the doubly lensed system, normalizing by the magnification factor of each image.

\(^{(e)}\) The absolute UV magnitued and the physical properties of AMORE6 from SED fitting are reported for only one of the two images (AMORE6-B), as the other one (AMORE6-A) suffers from large uncertainties, likely due to its location near bright galaxies as well as its smaller magnification factor (\(\mu = 39.32_{-3.48}^{+3.73}\), vs \(\mu = 77.69_{-5.92}^{+8.37}\) for AMORE6-B).

\(^{(f)}\) SFR inferred from H\(\beta\), larger than the value inferred from rest-frame UV luminosity – \((0.0186_{-0.0035}^{+0.0033}) ~\mathrm{M_\odot yr^{-1}}\) – or from averaging over the last 100 Myr of the best-fit star formation history – \((0.0038_{-0.0007}^{+0.0017}) ~\mathrm{M_\odot yr^{-1}}\) –, suporting the presence of a very young burst.

\(^{(g)}\) The reliability of the HeII line detection is hampered by the presence of a small blueshift relative to the Balmer lines, and by the extreme required EW (\(\gtrsim 200\) Å), therefore the authors safely consider the line undetected, placing a \(1\sigma\) upper limit of \(2.7 \times 10^{-10} ~\mathrm{erg \, s^{-1} \, cm^{-2}}\). Also note that the stellar continuum is undetected for this source.

\(^{(h)}\) Intrinsic line fluxes and upper limits are reported after applying corrections for lensing magnification and dust extinction, adopting \(A_\mathrm{V} = 0.12 \pm 0.04\) from their spectro-photometric analysis.

\(^{(i)}\) Assuming an extended star-formation history in which the stellar mass is built up steadily, but with a recent ~3 Myr burst of star formation, forming a mass of \((2.24_{-2.13}^{+1.48}) \times 10^7 ~\mathrm{M_\odot}\).

\(^{(j)}\) Though this system is not metal-free, the authors suggest that an effective temperature \(\gtrsim 80000\) K for the ionizing source is necessary (with no obvious sign of AGN heating), hardly explained with a standard IMF, and that exotic scenarios such as Pop III star formation within a mildly enriched halo would be consistent with the observation.

\(^{(k)}\) Spectroscopic redshift from Bunker et al. (2023).

\(^{(l)}\) From NIRSpec/IFU small aperture around HeII-emitting clump at \(\sim 0.5''\) from GN-z11; independent MSA measures yield a flux of \((3.4 \pm 0.9) \times 10^{-19} ~\mathrm{erg \, s^{-1} \, cm^{-2}}\) or an EW of \(98_{-52}^{+50}\) Å. However, uncertainties on the location of the MSA shutter, on the fraction of the putative HeII clump that entered the shutters and on absolute flux calibration prevent proper comparison.

\(^{(l)}\) From NIRSpec/IFU small \(0.24'' \times 0.24''\) square aperture around the HeII-emitting clump at \(\sim 0.5''\) from GN-z11; spectroscopy extracted from a larger aperture (aimed at capturing an additional and more extended HeII emission, possibly associated with a fainter and less significant clump about \(0.3''\) south of the HeII primary clump and \(0.4''\) east of GN-z11) yields \((5.0 \pm 0.8) \times 10^{-19} ~\mathrm{erg \, s^{-1} \, cm^{-2}}\), while independent MSA measures report a flux of \((3.4 \pm 0.9) \times 10^{-19} ~\mathrm{erg \, s^{-1} \, cm^{-2}}\). Uncertainties on the location of the MSA shutter, on the fraction of the putative HeII clump that entered the shutters, and on absolute flux calibration, together with the larger sensitivity of the MSA prism with respect than the IFU observation, prevent proper comparison.

\(^{(m)}\) As the continuum is totally undetected in the IFS medium-resolution spectra and only marginally detected in the low-resolution prism MSA spectrum (only yielding a 3\(\sigma\) lower limit on the EW of 15 Å from the small aperture), the EW here is estimated from photometry. The corresponding EWs from the larger aperture and from the MSA are respectively \(28.2_{-14.7}^{+14.5}\) Å (or \(> 12\) Å from spectroscopy), and \(98_{-52}^{+50}\) Å (\(145_{-55}^{+50}\) Å); also see Footnote \((l)\).

References

Bunker, Andrew J., Aayush Saxena, Alex J. Cameron, Chris J. Willott, Emma Curtis-Lake, Peter Jakobsen, Stefano Carniani, et al. 2023. “JADES NIRSpec Spectroscopy of GN-z11: Lyman-\(\alpha\) emission and possible enhanced nitrogen abundance in a z = 10.60 luminous galaxy” 677 (September): A88. https://doi.org/10.1051/0004-6361/202346159.

Cai, Sijia, Mingyu Li, Zheng Cai, Yunjing Wu, Fujiang Yu, Mark Dickinson, Fengwu Sun, et al. 2025. “A Metal-Free Galaxy at \(z = 3.19\)? Evidence of Late Population III Star Formation at Cosmic Noon.” arXiv e-Prints, July, arXiv:2507.17820. https://doi.org/10.48550/arXiv.2507.17820.

Cullen, F., A. C. Carnall, D. Scholte, D. J. McLeod, R. J. McLure, K. Z. Arellano-Córdova, T. M. Stanton, et al. 2025. “The JWST EXCELS survey: an extremely metal-poor galaxy at z = 8.271 hosting an unusual population of massive stars” 540 (3): 2176–94. https://doi.org/10.1093/mnras/staf838.

Fujimoto, Seiji, Rohan P. Naidu, John Chisholm, Hakim Atek, Ryan Endsley, Vasily Kokorev, Lukas J. Furtak, et al. 2025. “GLIMPSE: An Ultrafaint ≃10⁵ M⊙ Pop III Galaxy Candidate and First Constraints on the Pop III UV Luminosity Function at z ≃ 6.7” 989 (1): 46. https://doi.org/10.3847/1538-4357/ade9a1.

Maiolino, Roberto, Hannah Übler, Michele Perna, Jan Scholtz, Francesco D’Eugenio, Callum Witten, Nicolas Laporte, et al. 2024. “JADES. Possible Population III signatures at z = 10.6 in the halo of GN-z11” 687 (July): A67. https://doi.org/10.1051/0004-6361/202347087.

Mondal, Chayan, Kanak Saha, Anshuman Borgohain, Brent M. Smith, Rogier A. Windhorst, Naveen Reddy, Chian-Chou Chen, Keiichi Umetsu, and Rolf A. Jansen. 2025. “GNHeII J1236+6215: A He II \(\lambda\)1640 Emitting and Potentially LyC Leaking Galaxy at z = 2.9803 Unveiled through JWST and Keck Observations” 988 (2): 171. https://doi.org/10.3847/1538-4357/ade2cd.

Morishita, Takahiro, Zhaoran Liu, Massimo Stiavelli, Tommaso Treu, Pietro Bergamini, and Yechi Zhang. 2025. “Pristine Massive Star Formation Caught at the Break of Cosmic Dawn.” arXiv e-Prints, July, arXiv:2507.10521. https://doi.org/10.48550/arXiv.2507.10521.

Vanzella, E., F. Loiacono, P. Bergamini, U. Meštrić, M. Castellano, P. Rosati, M. Meneghetti, et al. 2023. “An extremely metal-poor star complex in the reionization era: Approaching Population III stars with JWST” 678 (October): A173. https://doi.org/10.1051/0004-6361/202346981.

Wang, Xin, Cheng Cheng, Junqiang Ge, Xiao-Lei Meng, Emanuele Daddi, Haojing Yan, Zhiyuan Ji, et al. 2024. “A Strong He II \(\lambda\)1640 Emitter with an Extremely Blue UV Spectral Slope at z = 8.16: Presence of Population III Stars?” 967 (2): L42. https://doi.org/10.3847/2041-8213/ad4ced.