The 21-cm power spectrum (PS) has been shown to be a powerful discriminant of reionization and co... more The 21-cm power spectrum (PS) has been shown to be a powerful discriminant of reionization and cosmic dawn astrophysical parameters. However, the 21-cm tomographic signal is highly non-Gaussian. Therefore there is additional information which is wasted if only the PS is used for parameter recovery. Here we showcase astrophysical parameter recovery directly from 21-cm images, using deep learning with convolutional neural networks (CNN). Using a data base of 2D images taken from 10 000 21-cm light-cones (each generated from different cosmological initial conditions), we show that a CNN is able to recover parameters describing the first galaxies: (i) Tvir , their minimum host halo virial temperatures (or masses) capable of hosting efficient star formation; (ii) ζ , their typical ionizing efficiencies; (iii) LX/SFR , their typical soft-band X-ray luminosity to star formation rate; and (iv) E0 , the minimum X-ray energy capable of escaping the galaxy into the IGM. For most of their allowed ranges, log Tvir and log LX/SFR are recovered with <1 per cent uncertainty, while ζ and E0 are recovered with ∼10 per cent uncertainty. Our results are roughly comparable to the accuracy obtained from Monte Carlo Markov Chain sampling of the PS with 21CMMC for the two mock observations analysed previously, although we caution that we do not yet include noise and foreground contaminants in this proof-of-concept study.
Dwarf galaxies are ideal laboratories to study the physics of the interstellar medium (ISM). Emis... more Dwarf galaxies are ideal laboratories to study the physics of the interstellar medium (ISM). Emission lines have been widely used to this aim. Retrieving the full information encoded in the spectra is therefore essential. This can be efficiently and reliably done using Machine Learning (ML) algorithms. Here, we apply the ML code GAME to MUSE (Multi Unit Spectroscopic Explorer) and PMAS (Potsdam Multi Aperture Spectrophotometer) integral field unit observations of two nearby blue compact galaxies: Henize 2-10 and IZw18. We derive spatially resolved maps of several key ISM physical properties. We find that both galaxies show a remarkably uniform metallicity distribution. Henize 2-10 is a star-forming-dominated galaxy, with a star formation rate (SFR) of about 1.2 M⊙ yr−1. Henize 2-10 features dense and dusty (AV up to 5–7 mag) star-forming central sites. We find IZw18 to be very metal-poor (Z = 1/20 Z⊙). IZw18 has a strong interstellar radiation field, with a large ionization parameter. We also use models of PopIII stars spectral energy distribution as a possible ionizing source for the He II λ4686 emission detected in the IZw18 NW component. We find that PopIII stars could provide a significant contribution to the line intensity. The upper limit to the PopIII star formation is 52 per cent of the total IZw18 SFR.
We present an updated, optimized version of GAME (GAlaxy Machine learning for Emission lines), a ... more We present an updated, optimized version of GAME (GAlaxy Machine learning for Emission lines), a code designed to infer key interstellar medium physical properties from emission line intensities of UV/optical/far infrared galaxy spectra. The improvements concern: (a) an enlarged spectral library including Pop III stars; (b) the inclusion of spectral noise in the training procedure, and (c) an accurate evaluation of uncertainties. We extensively validate the optimized code and compare its performance against empirical methods and other available emission line codes (PYQZ and HII-CHI-MISTRY) on a sample of 62 SDSS stacked galaxy spectra and 75 observed HII regions. Very good agreement is found for metallicity. However, ionization parameters derived by GAME tend to be higher. We show that this is due to the use of too limited libraries in the other codes. The main advantages of GAME are the simultaneous use of all the measured spectral lines, and the extremely short computational times. We finally discuss the code potential and limitations.
We present a new approach based on Supervised Machine Learning (SML) algorithms to infer key phys... more We present a new approach based on Supervised Machine Learning (SML) algorithms to infer key physical properties of galaxies (density, metallicity, column density and ionization parameter) from their emission line spectra. We introduce a numerical code (called game, GAlaxy Machine learning for Emission lines) implementing this method and test it extensively. game delivers excellent predictive performances, especially for estimates of metallicity and column densities. We compare game with the most widely used diagnostics (e.g. R_23 , [NII]λ6584 / Hα indicators) showing that it provides much better accuracy and wider applicability range. game is particularly suitable for use in combination with Integral Field Unit (IFU) spectroscopy, both for rest-frame optical/UV nebular lines and far-infrared/sub-mm lines arising from Photo-Dissociation Regions. Finally, game can also be applied to the analysis of synthetic galaxy maps built from numerical simulations.
High Energy Neutrino Astronomy has been revealed by a sudden change in the flavor composition abo... more High Energy Neutrino Astronomy has been revealed by a sudden change in the flavor composition above 30 TeV since 2013 by IceCube detector: the fast growth of spherical showers over atmospheric muon track signal in IceCube marked the revolution. However these discover didn't led to the promised Neutrino-Astronomy-Land yet. AGN flaring are not correlated with these high energy tens TeV-PeV events. Brightest persistent or pulsed galactic sources are missing while no point source arise in the lower energy sky. GRB events do not correlate within any minute-hour lapse time windows along any neutrino event. Moreover the astrophysical hard spectra whose exponent was expected at Fermi value of −2, seem to converge from −2.2 to a softer −2.7 or −3.0 value, also needed to avoid unobserved Glashow resonant neutrino at 6.3 PeV energy. Finally a key question arises: why within the ten UHE neutrino, those harder than 200 TeV events (whose timing structure would allow IceCube to disentangle any double tau neutrino imprint) don't double bang anyway? We suggest a main solution within a composite flux mostly ruled by prompt atmospheric neutrinos. Nevertheless in the very recent discover of 21 through-going (crossing) muons at hundreds TeVs, whose tracks are more aligned and telling, is shown a first narrow doublet (and some of correlated UHECR clustered source); this points – or give hints – for a non-negligible 10 − 20% astrophysical component, making neutrino astronomy already alive anyway.
In this paper we review all the up-to-date Ultra High Energy Cosmic Ray (UHECR) events reported b... more In this paper we review all the up-to-date Ultra High Energy Cosmic Ray (UHECR) events reported by AUGER, the Telescope Array (TA) and AGASA in common coordinate maps. We also confirm our earliest (2008–2013) model, where UHECRs mostly comprise light nuclei (namely He, Be, B), which explains the Virgo absence and confirms M82 as the main source for the Northern TA Hot Spot. Many more sources, such as NGC253 and several galactic sources, are possible candidates for most of the 376 UHECR events. Several correlated maps, already considered in recent years, are reported to show all the events, with their statistical correlation values.
Next generation telescopes such as the James Webb Space Telescope (JWST) and the Wide Field Infra... more Next generation telescopes such as the James Webb Space Telescope (JWST) and the Wide Field Infrared Survey Telescope (WFIRST) will enable us to study the first billion years of our Universe in unprecedented detail. In this work we use the astraeus (semi-numerical rAdiative tranSfer coupling of galaxy formaTion and Reionization in N-body dArk mattEr simUlationS) framework, that couples galaxy formation and reionization (for a wide range of reionization feedback models), to estimate the cosmic variance expected in the UV Luminosity Function (UV LF) and the Stellar Mass Function (SMF) in JWST surveys. We find that different reionization scenarios play a minor role in the cosmic variance. Most of the cosmic variance is completely driven by the underlying density field and increases above 100% for M UV ∼ −17.5 (−20) at z = 12 (6) for the JADES-deep survey (the deep JWST Advanced Extragalactic Survey with an area of 46 arcmin 2); the cosmic variance decreases with an increasing survey area roughly independently of redshift. We find that the faint-end slope of the Lyman Break Galaxies (LBGs) UV LF becomes increasingly shallower with increasing reionization feedback and show how JWST observations will be able to distinguish between different models of reionization feedback at z > 9, even accounting for cosmic variance. We also show the environments (in terms of density and ionization fields) of Lyman Break Galaxies during the EoR. Finally, we also provide a public software tool to allow interested readers to compute cosmic variance for different redshifts and survey areas.
We introduce a new self-consistent model of galaxy evolution and reionization, astraeus (semi-num... more We introduce a new self-consistent model of galaxy evolution and reionization, astraeus (semi-numerical rAdiative tranSfer coupling of galaxy formaTion and Reionization in N-body dArk mattEr simUlationS), which couples a state-of-the-art N-body simulation with the semi-analytical galaxy evolution delphi and the semi-numerical reionization scheme cifog. astraeus includes all the key processes of galaxy formation and evolution (including accretion, mergers, supernova and radia-tive feedback) and follows the time and spatial evolution of the ionized regions in the intergalactic medium (IGM). Importantly, it explores different radiative feedback models that cover the physically plausible parameter space, ranging from a weak and delayed to a strong and immediate reduction of gas mass available for star formation. From our simulation suite that covers the different radiative feedback prescriptions and ionization topologies, we find that radiative feedback continuously reduces star formation in galaxies with M h 10 9.5 M upon local reionization; larger mass halos are unaffected even for the strongest and immediate radiative feedback cases during reionization. For this reason, the ionization topologies of different radiative feedback scenarios differ only on scales smaller than 1 − 2 Mpc, and significant deviations are only found when physical parameters (e.g. the escape fraction of ionizing photons) are altered based on galactic properties. Finally, we find observables (the ultraviolet luminosity function, stellar mass function, reionization histories and ionization topolo-gies) are hardly affected by the choice of the used stellar population synthesis models that either model single stars or binaries.
The variabile star Delta Scorpii is in conjunction with the Sun at the end of November each year.... more The variabile star Delta Scorpii is in conjunction with the Sun at the end of November each year. We studied its magnitude by averaging the observations of 28 Nov-1 Dec from 1996 to 2013 using the coronograph LASCO C3 on-board the SOHO Satellite and we extended of four years, i.e. 25% of the total light curve, back to 1996, with respect to the present AAVSO dataset on this star. The 0.2 magnitude scatters of the single measurements have been studied and the sources of such disturbances are vignetting and diffraction patterns from the coronograph. The new data collected on Delta Scorpii show its minimum at mv=2.5 magnitudes for 1996 and 1997, confirming the values observed during the minimum of 2009, and the main periodicity of 11 years in the stellar variability.
Understanding the structure and physical properties of the Interstellar Medium (ISM) in galaxies,... more Understanding the structure and physical properties of the Interstellar Medium (ISM) in galaxies, especially at high redshift, is one of the major drivers of galaxy formation studies. Measurements of key properties as gas density, column density, metallicity, ionization parameter, and Habing flux, rely on galaxy spectra obtained through the most advanced telescopes (both earth-based and space-borne) and, in particular, on their emission lines. However, finding diagnostics that are free of significant systematic uncertainties remains an unsolved problem. Several attempts have been made to recover ISM physical properties by mean of diagnostics based on small, pre-selected subsets of emission line ratios. Most of these previous works focused on ionized nebulae, and have obtained diagnostics for the physical properties of galaxies based only on the strongest nebular emission lines coming from extra-galactic HII regions and star-forming galaxies. The main purpose of this work is to reconstruct key ISM physical properties of galaxies from their spectra. The aim is to maximize the information that can be extracted from such data by using not only few specific and pre-selected emission lines, but the full information encoded in the spectra. This is now possible thanks to the combination of powerful Supervised Machine Learning (ML) algorithms and large synthetic spectra libraries. In order to achieve this goal, I have developed a code called game (GAlaxy Machine learning for Emission lines), a new fast method to reconstruct the ISM physical properties by using all the information carried by the emission lines intensities present in the available spectrum. The library included in this code covers a very large range of plausible ISM physical properties to accurately describe the physics both of ionized regions and of other phases (i.e neutral, molecular) of the ISM. The strength of the method relies on the fact that the ml algorithm can learn from all the lines present in a spectrum, including the weakest ones as those coming for example from neutral ISM components. I verified that with ML it is possible to set strong constraints on the properties of the different phases from observed spectra. GAME has been extensively tested, and shown to deliver excellent predictive performances when applied to synthetic spectra. A ML approach will become fundamental with upcoming high-quality spectra, including also faint lines of high-redshift galaxies, from new facilities such as the James Webb Space Telescope (JWST) and the Extremely Large Telescope (ELT). The astrophysical community will be therefore into an era where ml algorithms and Big Data Analytics will become extremely useful tools in the data-mining process. This is already the case for local observations where Integral Field Units (IFUs) are already able to provide observations containing tens of thousands of spaxels. A notable study case is the ISM of local Blue Compact Galaxies (BCGs), a subclass of dwarf galaxies. In fact, since BCGs are low-metallicity, compact, star-forming systems, they are thought to represent local analogues of early galaxies that will become soon observable in greater detail (e.g. with JWST). Thus, ISM studies of local BCGs can be used as benchmarks for understanding the structure, formation, and evolution of high-redshift galaxies. In addition to a general description of the ML algorithm and the GAME code, I will show the first game results concerning the interpretation of high-quality IFU spectra of BCGs.
The 21-cm power spectrum (PS) has been shown to be a powerful discriminant of reionization and co... more The 21-cm power spectrum (PS) has been shown to be a powerful discriminant of reionization and cosmic dawn astrophysical parameters. However, the 21-cm tomographic signal is highly non-Gaussian. Therefore there is additional information which is wasted if only the PS is used for parameter recovery. Here we showcase astrophysical parameter recovery directly from 21-cm images, using deep learning with convolutional neural networks (CNN). Using a data base of 2D images taken from 10 000 21-cm light-cones (each generated from different cosmological initial conditions), we show that a CNN is able to recover parameters describing the first galaxies: (i) Tvir , their minimum host halo virial temperatures (or masses) capable of hosting efficient star formation; (ii) ζ , their typical ionizing efficiencies; (iii) LX/SFR , their typical soft-band X-ray luminosity to star formation rate; and (iv) E0 , the minimum X-ray energy capable of escaping the galaxy into the IGM. For most of their allowed ranges, log Tvir and log LX/SFR are recovered with <1 per cent uncertainty, while ζ and E0 are recovered with ∼10 per cent uncertainty. Our results are roughly comparable to the accuracy obtained from Monte Carlo Markov Chain sampling of the PS with 21CMMC for the two mock observations analysed previously, although we caution that we do not yet include noise and foreground contaminants in this proof-of-concept study.
Dwarf galaxies are ideal laboratories to study the physics of the interstellar medium (ISM). Emis... more Dwarf galaxies are ideal laboratories to study the physics of the interstellar medium (ISM). Emission lines have been widely used to this aim. Retrieving the full information encoded in the spectra is therefore essential. This can be efficiently and reliably done using Machine Learning (ML) algorithms. Here, we apply the ML code GAME to MUSE (Multi Unit Spectroscopic Explorer) and PMAS (Potsdam Multi Aperture Spectrophotometer) integral field unit observations of two nearby blue compact galaxies: Henize 2-10 and IZw18. We derive spatially resolved maps of several key ISM physical properties. We find that both galaxies show a remarkably uniform metallicity distribution. Henize 2-10 is a star-forming-dominated galaxy, with a star formation rate (SFR) of about 1.2 M⊙ yr−1. Henize 2-10 features dense and dusty (AV up to 5–7 mag) star-forming central sites. We find IZw18 to be very metal-poor (Z = 1/20 Z⊙). IZw18 has a strong interstellar radiation field, with a large ionization parameter. We also use models of PopIII stars spectral energy distribution as a possible ionizing source for the He II λ4686 emission detected in the IZw18 NW component. We find that PopIII stars could provide a significant contribution to the line intensity. The upper limit to the PopIII star formation is 52 per cent of the total IZw18 SFR.
We present an updated, optimized version of GAME (GAlaxy Machine learning for Emission lines), a ... more We present an updated, optimized version of GAME (GAlaxy Machine learning for Emission lines), a code designed to infer key interstellar medium physical properties from emission line intensities of UV/optical/far infrared galaxy spectra. The improvements concern: (a) an enlarged spectral library including Pop III stars; (b) the inclusion of spectral noise in the training procedure, and (c) an accurate evaluation of uncertainties. We extensively validate the optimized code and compare its performance against empirical methods and other available emission line codes (PYQZ and HII-CHI-MISTRY) on a sample of 62 SDSS stacked galaxy spectra and 75 observed HII regions. Very good agreement is found for metallicity. However, ionization parameters derived by GAME tend to be higher. We show that this is due to the use of too limited libraries in the other codes. The main advantages of GAME are the simultaneous use of all the measured spectral lines, and the extremely short computational times. We finally discuss the code potential and limitations.
We present a new approach based on Supervised Machine Learning (SML) algorithms to infer key phys... more We present a new approach based on Supervised Machine Learning (SML) algorithms to infer key physical properties of galaxies (density, metallicity, column density and ionization parameter) from their emission line spectra. We introduce a numerical code (called game, GAlaxy Machine learning for Emission lines) implementing this method and test it extensively. game delivers excellent predictive performances, especially for estimates of metallicity and column densities. We compare game with the most widely used diagnostics (e.g. R_23 , [NII]λ6584 / Hα indicators) showing that it provides much better accuracy and wider applicability range. game is particularly suitable for use in combination with Integral Field Unit (IFU) spectroscopy, both for rest-frame optical/UV nebular lines and far-infrared/sub-mm lines arising from Photo-Dissociation Regions. Finally, game can also be applied to the analysis of synthetic galaxy maps built from numerical simulations.
High Energy Neutrino Astronomy has been revealed by a sudden change in the flavor composition abo... more High Energy Neutrino Astronomy has been revealed by a sudden change in the flavor composition above 30 TeV since 2013 by IceCube detector: the fast growth of spherical showers over atmospheric muon track signal in IceCube marked the revolution. However these discover didn't led to the promised Neutrino-Astronomy-Land yet. AGN flaring are not correlated with these high energy tens TeV-PeV events. Brightest persistent or pulsed galactic sources are missing while no point source arise in the lower energy sky. GRB events do not correlate within any minute-hour lapse time windows along any neutrino event. Moreover the astrophysical hard spectra whose exponent was expected at Fermi value of −2, seem to converge from −2.2 to a softer −2.7 or −3.0 value, also needed to avoid unobserved Glashow resonant neutrino at 6.3 PeV energy. Finally a key question arises: why within the ten UHE neutrino, those harder than 200 TeV events (whose timing structure would allow IceCube to disentangle any double tau neutrino imprint) don't double bang anyway? We suggest a main solution within a composite flux mostly ruled by prompt atmospheric neutrinos. Nevertheless in the very recent discover of 21 through-going (crossing) muons at hundreds TeVs, whose tracks are more aligned and telling, is shown a first narrow doublet (and some of correlated UHECR clustered source); this points – or give hints – for a non-negligible 10 − 20% astrophysical component, making neutrino astronomy already alive anyway.
In this paper we review all the up-to-date Ultra High Energy Cosmic Ray (UHECR) events reported b... more In this paper we review all the up-to-date Ultra High Energy Cosmic Ray (UHECR) events reported by AUGER, the Telescope Array (TA) and AGASA in common coordinate maps. We also confirm our earliest (2008–2013) model, where UHECRs mostly comprise light nuclei (namely He, Be, B), which explains the Virgo absence and confirms M82 as the main source for the Northern TA Hot Spot. Many more sources, such as NGC253 and several galactic sources, are possible candidates for most of the 376 UHECR events. Several correlated maps, already considered in recent years, are reported to show all the events, with their statistical correlation values.
Next generation telescopes such as the James Webb Space Telescope (JWST) and the Wide Field Infra... more Next generation telescopes such as the James Webb Space Telescope (JWST) and the Wide Field Infrared Survey Telescope (WFIRST) will enable us to study the first billion years of our Universe in unprecedented detail. In this work we use the astraeus (semi-numerical rAdiative tranSfer coupling of galaxy formaTion and Reionization in N-body dArk mattEr simUlationS) framework, that couples galaxy formation and reionization (for a wide range of reionization feedback models), to estimate the cosmic variance expected in the UV Luminosity Function (UV LF) and the Stellar Mass Function (SMF) in JWST surveys. We find that different reionization scenarios play a minor role in the cosmic variance. Most of the cosmic variance is completely driven by the underlying density field and increases above 100% for M UV ∼ −17.5 (−20) at z = 12 (6) for the JADES-deep survey (the deep JWST Advanced Extragalactic Survey with an area of 46 arcmin 2); the cosmic variance decreases with an increasing survey area roughly independently of redshift. We find that the faint-end slope of the Lyman Break Galaxies (LBGs) UV LF becomes increasingly shallower with increasing reionization feedback and show how JWST observations will be able to distinguish between different models of reionization feedback at z > 9, even accounting for cosmic variance. We also show the environments (in terms of density and ionization fields) of Lyman Break Galaxies during the EoR. Finally, we also provide a public software tool to allow interested readers to compute cosmic variance for different redshifts and survey areas.
We introduce a new self-consistent model of galaxy evolution and reionization, astraeus (semi-num... more We introduce a new self-consistent model of galaxy evolution and reionization, astraeus (semi-numerical rAdiative tranSfer coupling of galaxy formaTion and Reionization in N-body dArk mattEr simUlationS), which couples a state-of-the-art N-body simulation with the semi-analytical galaxy evolution delphi and the semi-numerical reionization scheme cifog. astraeus includes all the key processes of galaxy formation and evolution (including accretion, mergers, supernova and radia-tive feedback) and follows the time and spatial evolution of the ionized regions in the intergalactic medium (IGM). Importantly, it explores different radiative feedback models that cover the physically plausible parameter space, ranging from a weak and delayed to a strong and immediate reduction of gas mass available for star formation. From our simulation suite that covers the different radiative feedback prescriptions and ionization topologies, we find that radiative feedback continuously reduces star formation in galaxies with M h 10 9.5 M upon local reionization; larger mass halos are unaffected even for the strongest and immediate radiative feedback cases during reionization. For this reason, the ionization topologies of different radiative feedback scenarios differ only on scales smaller than 1 − 2 Mpc, and significant deviations are only found when physical parameters (e.g. the escape fraction of ionizing photons) are altered based on galactic properties. Finally, we find observables (the ultraviolet luminosity function, stellar mass function, reionization histories and ionization topolo-gies) are hardly affected by the choice of the used stellar population synthesis models that either model single stars or binaries.
The variabile star Delta Scorpii is in conjunction with the Sun at the end of November each year.... more The variabile star Delta Scorpii is in conjunction with the Sun at the end of November each year. We studied its magnitude by averaging the observations of 28 Nov-1 Dec from 1996 to 2013 using the coronograph LASCO C3 on-board the SOHO Satellite and we extended of four years, i.e. 25% of the total light curve, back to 1996, with respect to the present AAVSO dataset on this star. The 0.2 magnitude scatters of the single measurements have been studied and the sources of such disturbances are vignetting and diffraction patterns from the coronograph. The new data collected on Delta Scorpii show its minimum at mv=2.5 magnitudes for 1996 and 1997, confirming the values observed during the minimum of 2009, and the main periodicity of 11 years in the stellar variability.
Understanding the structure and physical properties of the Interstellar Medium (ISM) in galaxies,... more Understanding the structure and physical properties of the Interstellar Medium (ISM) in galaxies, especially at high redshift, is one of the major drivers of galaxy formation studies. Measurements of key properties as gas density, column density, metallicity, ionization parameter, and Habing flux, rely on galaxy spectra obtained through the most advanced telescopes (both earth-based and space-borne) and, in particular, on their emission lines. However, finding diagnostics that are free of significant systematic uncertainties remains an unsolved problem. Several attempts have been made to recover ISM physical properties by mean of diagnostics based on small, pre-selected subsets of emission line ratios. Most of these previous works focused on ionized nebulae, and have obtained diagnostics for the physical properties of galaxies based only on the strongest nebular emission lines coming from extra-galactic HII regions and star-forming galaxies. The main purpose of this work is to reconstruct key ISM physical properties of galaxies from their spectra. The aim is to maximize the information that can be extracted from such data by using not only few specific and pre-selected emission lines, but the full information encoded in the spectra. This is now possible thanks to the combination of powerful Supervised Machine Learning (ML) algorithms and large synthetic spectra libraries. In order to achieve this goal, I have developed a code called game (GAlaxy Machine learning for Emission lines), a new fast method to reconstruct the ISM physical properties by using all the information carried by the emission lines intensities present in the available spectrum. The library included in this code covers a very large range of plausible ISM physical properties to accurately describe the physics both of ionized regions and of other phases (i.e neutral, molecular) of the ISM. The strength of the method relies on the fact that the ml algorithm can learn from all the lines present in a spectrum, including the weakest ones as those coming for example from neutral ISM components. I verified that with ML it is possible to set strong constraints on the properties of the different phases from observed spectra. GAME has been extensively tested, and shown to deliver excellent predictive performances when applied to synthetic spectra. A ML approach will become fundamental with upcoming high-quality spectra, including also faint lines of high-redshift galaxies, from new facilities such as the James Webb Space Telescope (JWST) and the Extremely Large Telescope (ELT). The astrophysical community will be therefore into an era where ml algorithms and Big Data Analytics will become extremely useful tools in the data-mining process. This is already the case for local observations where Integral Field Units (IFUs) are already able to provide observations containing tens of thousands of spaxels. A notable study case is the ISM of local Blue Compact Galaxies (BCGs), a subclass of dwarf galaxies. In fact, since BCGs are low-metallicity, compact, star-forming systems, they are thought to represent local analogues of early galaxies that will become soon observable in greater detail (e.g. with JWST). Thus, ISM studies of local BCGs can be used as benchmarks for understanding the structure, formation, and evolution of high-redshift galaxies. In addition to a general description of the ML algorithm and the GAME code, I will show the first game results concerning the interpretation of high-quality IFU spectra of BCGs.
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