IAS-LAB PUBLICATIONS
Euclid: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field
Authors: AREA MIN. 02 - Scienze fisiche; ASTRONOMY & ASTROPHYSICS###0004-6361; JNB-1152-2023; MYS-2354-2025; EFH-6710-2022; OMN-3792-2025; GAV-3687-2022; FYJ-4908-2022; FHL-5547-2022; MMS-5823-2025; JBR-8488-2023; JMS-1539-2023; MXB-2135-2025; CGD-2351-2022; JAX-2768-2023; CKU-5761-2022; H-4394-2019; DXZ-7810-2022; LEQ-1557-2024; DWU-8294-2022; D-1237-2017; EPI-1133-2022; AGZ-3259-2022; LHK-9354-2024; DVB-8405-2022; AFJ-2074-2022; MDG-9557-2025; GMD-3106-2022; ILM-3517-2023; DWQ-9372-2022; MYW-7907-2025; INU-5783-2023; DUZ-7625-2022; DFW-8877-2022; IFC-0531-2023; LXV-7382-2024; KJZ-3935-2024; FTV-5671-2022; DRO-1214-2022; FXH-0557-2022; IUA-7590-2023; DYG-8338-2022; HWB-5458-2023; MNN-3541-2025; EBD-7764-2022; MQB-8395-2025; HZW-5449-2023; DXA-1243-2022; GEH-7593-2022; GBG-9412-2022; DYF-3433-2022; HFV-0042-2022; FYH-4361-2022; FYH-7305-2022; MYL-2765-2025; DWY-3410-2022; DWN-4354-2022; CHZ-5646-2022; L-2472-2017; EQY-9285-2022; AAD-3011-2021; H-2913-2012; DAV-8065-2022; GBC-8404-2022; FZO-1254-2022; FYJ-9637-2022; CEY-5520-2022; C-4378-2014; EKA-7986-2022; IUT-7926-2023; IUQ-9509-2023; DVB-2560-2022; L-8385-2017; JWI-9457-2024; M-2616-2015; CJD-7824-2022; HWT-5982-2023; GBO-0318-2022; E-2727-2014; L-8237-2014; IVA-4275-2023; EOV-3838-2022; B-4650-2017; HZM-8546-2023; HTG-8587-2023; H-8587-2015; B-4348-2013; DVC-6323-2022; HQF-6437-2023; FZL-7353-2022; A-2693-2010; EVT-3533-2022; CNE-2384-2022; HLX-2021-2023; HKB-2933-2023; EUO-2530-2022; EUK-3820-2022; J-3686-2012; CPC-6980-2022; AAR-6622-2021; IBV-9243-2023; CQF-5798-2022; DXA-1952-2022; HPT-5858-2023; GBB-1832-2022; OVM-5938-2025; GQH-6424-2022; ABF-7029-2021; DWK-1716-2022; JGR-4365-2023; CTE-6775-2022; CSK-3817-2022; FBF-5584-2022; FBE-0351-2022; S-8590-2017; CTZ-4163-2022; GBH-2365-2022; EYY-4006-2022; FBM-0217-2022; GZL-0460-2022; DWS-1040-2022; DXH-0671-2022; FFG-2233-2022; GEK-4486-2022; CYT-5449-2022; FEG-4298-2022; DUU-4676-2022; B-8502-2016; LYD-9061-2024; GFM-0308-2022; A-2699-2012; GAU-7672-2022; FIV-3763-2022; MTO-5925-2025; DWZ-6747-2022; DFQ-7859-2022; AAH-9937-2020; V-6916-2017; MWK-2416-2025; AAX-3485-2021; D-1300-2016; GNG-7078-2022; FNC-4379-2022; DFC-8070-2022; FLD-9518-2022; DVP-3997-2022; KEK-6332-2024; KJY-7272-2024; DWT-4779-2022; KNP-2716-2024; DJO-8166-2022; MNN-0179-2025; KFB-7397-2024; ABB-2322-2020; DKF-4281-2022; HTJ-4919-2023; DWD-4131-2022; DLB-6897-2022; HTM-1531-2023; GBD-7573-2022; MTQ-2344-2025; IVG-7504-2023; FSY-2184-2022; DMX-5934-2022; ABC-8644-2021; DNY-0415-2022; K-4114-2015; OON-3882-2025; DNW-6364-2022; DXL-4304-2022; MXB-9468-2025; GCT-2940-2022; DXO-8435-2022; FXS-9180-2022; FXG-6905-2022; H-1761-2016; DXM-5348-2022; GFJ-2734-2022; FZX-9985-2022; IZJ-2041-2023; GBV-4959-2022; GWX-9207-2022; OWM-0849-2025; KKE-9686-2024; NES-1075-2025; EAA-4768-2022; LGB-5701-2024; L-8068-2014; Q-2220-2015; T-7378-2018; AAB-2503-2019; GCB-5227-2022; DYT-7473-2022; HNI-8187-2023; GCA-5567-2022; FCD-8153-2022; JCG-3503-2023; NBS-7222-2025; ABD-6783-2021; EAZ-0566-2022; O-9396-2015; DTO-7937-2022; LWL-2178-2024; FQI-9285-2022; IWG-9653-2023; FVK-3262-2022; DYK-4428-2022; MXA-3751-2025; 58666622600; 58419113700; 57535859700; 58544914400; 59137911400; 57190942170; 57205730219; 57958980000; 57207846185; 7003485288; 57191290632; 58918946600; 57210265918; 55731742600; 55929371000; 58911394800; 8856476200; 7801607411; 7101983827; 6602458029; 59636105400; 59317606600; 55862177400; 55668778200; 59317261300; 57322480400; 57473067700; 55539553700; 57188806951; 36126412600; 57193489486; 7005525798; 56949991000; 6603351766; 57199319204; 55932248600; 22836264500; 57211567711; 13204971700; 12786945200; 7005244190; 25951796800; 7401938216; 55822387500; 6602409206; 57192921002; 57204700965; 8833942000; 57206423651; 56153006200; 57221950386; 57213830231; 7004666481; 57193558463; 6701685211; 7006398476; 55976971800; 35241782000; 57218513471; 10738797800; 7003825248; 6701409861; 14629998500; 56176939800; 57220414927; 24482926400; 6505819655; 57225389323; 35421870300; 6602293713; 6701447926; 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14050522100; 56118600700; 58095754900; 57203234808; 55913343900; 57544565000; 7003604949; 57203250534; 15770290900; 6602930238; 57190439701; 7006538931; 8842216700; 6506955003; 55337191500; 7402364894; 57225899623; 57190443165; 8915699600; 6603819159; 7004160690; 57219119015; 56881732300; 15129157800; 48663031800; 57218941481; 13407890400; 14063887300; 54797318800; 55845420026; 6602208520; 6602315420; 35100980600; 14823864100; 58502049600; 57220082325; 58937209900; 17436196900; 57203391123; 57191960842; 6701439004; 6602565951; 57191419742; 14832839700; 56286395400; 59730206000; 7101771030; 8042894900; 9333441800; 6603819488; 57198031424; 7102775303; 57220131178; 56512377200; 7003963996; 55541304900
Journal: ASTRONOMY & ASTROPHYSICS
Published: 2025
DOI: 10.1051/0004-6361/202453152
The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg2 of the sky. Detecting this many lenses by visual inspection with professional astronomers and citizen scientists alone is infeasible. As a result, machine learning algorithms, particularly convolutional neural networks (CNNs), have been used as an automated method of detecting strong lenses, and have proven fruitful in finding galaxy-galaxy strong lens candidates, such that the usage of CNNs in lens identification has increased. We identify the major challenge to be the automatic detection of galaxy-galaxy strong lenses while simultaneously maintaining a low false positive rate, thus producing a pure and complete sample of strong lens candidates from Euclid with a limited need for visual inspection. One aim of this research is to have a quantified starting point on the achieved purity and completeness with our current version of CNN-based detection pipelines for the VIS images of EWS. This work is vital in preparing our CNN-based detection pipelines to be able to produce a pure sample of the >100 000 strong gravitational lensing systems widely predicted for Euclid. We select all sources with VIS IE < 23 mag from the Euclid Early Release Observation imaging of the Perseus field. We apply a range of CNN architectures to detect strong lenses in these cutouts. All our networks perform extremely well on simulated data sets and their respective validation sets. However, when applied to real Euclid imaging, the highest lens purity is just ∼11%. Among all our networks, the false positives are typically identifiable by human volunteers as, for example, spiral galaxies, multiple sources, and artifacts, implying that improvements are still possible, perhaps via a second, more interpretable lens selection filtering stage. There is currently no alternative to human classification of CNN-selected lens candidates. Given the expected ∼105 lensing systems in Euclid, this implies 106 objects for human classification, which while very large is not in principle intractable and not without precedent.
Volume: 696
Keywords: dark matter; large-scale structure of Universe; methods: data analysis; surveys;
Euclid: Early Release Observations – Interplay between dwarf galaxies and their globular clusters in the Perseus galaxy cluster☆
Authors: AREA MIN. 02 - Scienze fisiche; ASTRONOMY & ASTROPHYSICS###0004-6361; GEH-7593-2022; GDD-0521-2022; FZP-9871-2022; DWB-0787-2022; DXH-1132-2022; OWP-8743-2025; DWO-2405-2022; ABE-1497-2020; FZK-6500-2022; OFI-3304-2025; GFK-2340-2022; DVE-7652-2022; MYY-8327-2025; NWP-1675-2025; H-4394-2019; MFP-6153-2025; GDB-0545-2022; HZW-5449-2023; H-2913-2012; NYV-4209-2025; MWG-8499-2025; NAA-8765-2025; DWK-1716-2022; Z-4828-2019; DBY-6056-2022; MDH-6494-2025; KPF-2019-2024; EJM-8740-2022; OWJ-2849-2025; MFN-2097-2025; CDR-2303-2022; CEY-5520-2022; ENZ-8382-2022; NIH-4106-2025; EKA-7986-2022; MPK-2619-2025; LXX-3952-2024; IUQ-9509-2023; AAO-6325-2021; EMQ-6210-2022; OXU-5068-2025; EOE-6462-2022; ENY-9969-2022; HTU-7350-2023; OTR-9915-2025; PFB-7368-2025; GBO-0318-2022; JTJ-0113-2023; JGB-4169-2023; OYX-1138-2025; IVA-4275-2023; OWA-5096-2025; HZM-8546-2023; HOH-0341-2023; IRQ-6937-2023; HTG-8587-2023; H-8587-2015; B-4348-2013; MLE-5410-2025; OUB-9437-2025; OUQ-7327-2025; AGZ-3259-2022; NKT-5952-2025; PGO-8625-2026; PCA-2324-2025; CNE-2384-2022; IDQ-0489-2023; GBB-1963-2022; EUO-2530-2022; LZM-1403-2025; EUK-3820-2022; EVA-7948-2022; LQC-6518-2024; OXU-8438-2025; ETK-1170-2022; IBV-9243-2023; CQF-5798-2022; CQN-5681-2022; OWH-3656-2025; HPT-5858-2023; JWF-2506-2024; OWJ-3544-2025; PDR-5897-2025; CQR-5759-2022; HTH-2171-2023; CTE-6775-2022; CSK-3817-2022; FBF-5584-2022; EYM-5386-2022; ORP-2127-2025; FBV-0790-2022; S-8590-2017; CTZ-4163-2022; GBH-2365-2022; DWQ-9372-2022; AAT-5867-2020; DWS-1040-2022; DXH-0671-2022; FFG-2233-2022; CYT-5449-2022; OOP-8239-2025; MKH-2584-2025; B-8502-2016; HXO-8043-2023; DAV-8065-2022; Q-5758-2017; LYD-9061-2024; GFM-0308-2022; A-2699-2012; GAU-7672-2022; FIV-3763-2022; FLK-4707-2022; HLM-5105-2023; OYW-4457-2025; DEG-2174-2022; U-7309-2018; MWK-2416-2025; AAX-3485-2021; JBX-4604-2023; FNO-5530-2022; GNG-7078-2022; FNC-4379-2022; FLD-9518-2022; OUB-8222-2025; DVP-3997-2022; FNA-5485-2022; FQI-9285-2022; KJY-7272-2024; DWT-4779-2022; KNP-2716-2024; DJO-8166-2022; FNB-0821-2022; OVR-3480-2025; HTJ-4919-2023; MAJ-2831-2025; DLB-6897-2022; HTM-1531-2023; OWI-2937-2025; DMG-4306-2022; IVG-7504-2023; FSY-2184-2022; DMX-5934-2022; DNQ-7220-2022; DNY-0415-2022; OWQ-1639-2025; IHD-3727-2023; OON-3882-2025; DNW-6364-2022; DXL-4304-2022; MXB-9468-2025; DXO-8435-2022; JVJ-6571-2024; FXG-6905-2022; HFW-5845-2022; MWY-9362-2025; DRA-2090-2022; NKY-6871-2025; OWD-1829-2025; NIO-4355-2025; DZW-2293-2022; HPZ-9398-2023; FZJ-5145-2022; KKE-9686-2024; EAA-4768-2022; LGB-5701-2024; L-8068-2014; MQB-6975-2025; GDK-6495-2022; JEZ-2766-2023; KJV-8369-2024; AAB-2503-2019; KLN-4310-2024; GCB-5227-2022; DYT-7473-2022; OAE-4195-2025; A-9058-2016; MRJ-8187-2025; NDK-0367-2025; JCG-3503-2023; PGR-2221-2026; EEM-5070-2022; EAZ-0566-2022; EFP-5424-2022; NYS-2102-2025; DTO-7937-2022; JHF-8266-2023; FVK-3262-2022
Journal: ASTRONOMY & ASTROPHYSICS
Published: 2025
DOI: 10.1051/0004-6361/202554667
Volume: 703
For what algebraic systems does a useful privacy homomorphism exist?
Authors: Grazian Valentina; Tortora Antonio; Tota Maria
Journal: AIMS MATHEMATICS
Published: 2025
DOI: 10.3934/math.2025440
Homomorphic encryption plays a crucial role in the challenging problem of privacy preservation. In this survey, we describe a number of homomorphic schemes providing the relevant definitions to make the topic accessible to both cryptographers and mathematicians. We classify the schemes according to the timeline of appearance and, for some of them, we verify that they are correct with respect to decryption and evaluation, providing proofs or references. Recent research directions are also briefly discussed in this context.
Volume: 10 Pages: 9539-9562
Keywords: cloud computing; fully homomorphic encryption; privacy preservation;
Euclid preparation LXXIII. Spatially resolved stellar populations of local galaxies with Euclid: A proof of concept using synthetic images with the TNG50 simulation
Authors: AREA MIN. 02 - Scienze fisiche; Non assegn; AREA MIN. 14 - Scienze politiche e sociali; AREA MIN. 01 - Scienze matematiche e informatiche; AREA MIN. 09 - Ingegneria industriale e dell'informazione; AREA MIN. 06 - Scienze mediche; ASTRONOMY & ASTROPHYSICS###0004-6361; 57202215260; 55929371000; 56261663500; 57189593362; 58817124800; 6602409206; 6701673913; 56426999100; 55941325100; 7005183546; 6603186973; 7003910265; 57200793436; 7402054273; 55178467000; 55538241000; 56033190100; 7005317106; 56234721400; 35494536400; 7006440295; 57222380960; 6603939854; 15754453800; 57193523315; 57204700965; 7004408758; 60098455000; 35957375500; 57203047758; 57103783400; 6701409861; 56176939800; 57220414927; 24482926400; 57225389323; 7004185737; 55600275300; 6602293713; 6701447926; 7004168457; 7004279376; 55543112300; 35117442400; 57219376526; 56592859600; 8316050500; 57193414472; 57090221700; 24439181000; 55948641800; 54924573500; 7007018277; 56260193000; 55543336500; 37121732700; 6507398813; 55757270100; 8856476200; 59636105400; 7004529134; 26663174300; 6603213706; 6602521535; 7006071419; 57212263363; 6701458135; 6506323808; 6601991850; 6602678698; 6602348000; 56181792800; 57202592808; 57200514857; 24587025200; 9639653200; 56239931500; 36627225700; 6506341877; 56592156500; 24173378000; 14630273900; 36657273100; 8527480900; 57203599140; 12809267200; 9270789600; 14008117700; 7202555066; 16024707000; 6603380199; 36663730200; 55539553700; 35425530800; 55885669700; 35227493200; 37123976000; 6701865592; 55578049300; 56216916000; 7102120605; 6603602446; 56149076900; 6603205767; 6603770482; 56403356600; 36195926600; 35070066100; 14058603600; 10239419900; 14025617800; 6506385309; 36933808800; 56463558800; 55779479900; 13407562800; 7102174334; 14056466700; 7102846243; 36542679900; 55665939900; 7005525798; 14832846900; 7004208543; 7102775303; 35299820900; 7004629002; 14050522100; 56118600700; 58095754900; 57203234808; 55913343900; 57544565000; 57203250534; 6602930238; 57190439701; 7006538931; 8842216700; 6506955003; 55337191500; 7402364894; 57225899623; 57190443165; 8915699600; 6603819159; 7004160690; 57219119015; 15129157800; 48663031800; 8833942000; 57218941481; 13407890400; 14063887300; 6506381727; 54797318800; 55845420026; 55435714500; 6602208520; 6602315420; 14823864100; 58502049600; 57220082325; 55414427600; 58937209900; 7004109829; 17436196900; 57203391123; 57191960842; 6602565951; 6506892358; 57191419742; 6603196124; 56286395400; 10244106400; 7101771030; 8042894900; 9333441800; 36905906400; 6603819488; 57198031424; 9244606800; 58696967900; 57845873200; 26326923900; 57220131178; 57203270249; 56512377200; 35194662000; 7003963996; 57203063840; 35387346400; 46461103400; 42260895600; 36730729100; 6701547091; 56818885600; 23027139300; 14820320500; 59421337500; 7006764136; 57205381665; 57214989073; 6602458029; 57193874792; 9337037600; 57211860571; 7103030457; 56653598400; 58621464800; 9335763100; 35112881300; 34569356300; 57199061795; 55976971800; 24074399500; 58112082700; 57218304683; 7003900144; 55420010100; 25723173900; 7004144883; 7003645652; 57193849410; 55944081300; 56242244500; 7005222927; 15131601400; 14630220200; 58030558500; 7202545187; 36674792500; 55505778800; 8833942900; 55741929700; 23050749700; 57224183772; 36966126400; 59774401700; 57218097629; 56153170500; 26642611400; 57193558463; 27169527700; 57213569252; 57892676500; 57213763435; 57219756241; 6701851021; 57218549969; 57210924350; 6508080858; 6701309093; 6701685211; 6603292899; 6506425834; 22951241500; 56383649900; 7101983827; 55246080700; 7006221760; 57218766355; 35422761600; 57189089616; 35463408300; 57192212259; 7003762062; 56285291900; 7101903552; 16031797900; 57222902516; 55672552800; 10642144300; 57207198854; 57201003368; 58696967800; 55965473600; 7005050491; 57211858405; 7102146471; 6603851717; 6701718244; 56448179900; 57132747000; 58483607200; 6504758580; 14632583100; 57215412075; 55195649400
Journal: 26750
Published: 2025
DOI: 10.1051/0004-6361/202554516
The European Space Agency’s Euclid mission will observe approximately 14 000 deg2 of the extragalactic sky and deliver high-quality imaging of a large number of galaxies. The depth and high spatial resolution of the data will enable a detailed analysis of the stellar population properties of local galaxies through spatially resolved spectral energy distribution (SED) fitting. In this study, we test our pipeline for spatially resolved SED fitting using synthetic images of Euclid, LSST, and GALEX generated from the TNG50 simulation using the SKIRT 3D radiative transfer code. Our pipeline uses functionalities in piXedfit for processing the simulated data cubes and carrying out SED fitting. We apply our pipeline to 25 simulated galaxies at z ∼ 0 to recover their resolved stellar population properties. For each galaxy, we produce three types of data cubes: GALEX + LSST + Euclid, LSST + Euclid, and Euclid-only. We performed the SED fitting tests with two stellar population synthesis (SPS) models in a Bayesian framework. Because the age, metallicity (Z), and dust attenuation estimates are biased when applying only classical formulations of flat priors (even with the combined GALEX + LSST + Euclid data), we examined the effects of additional physically motivated priors in the forms of mass-age and mass-metallicity relations, constructed using a combination of empirical and simulated data. Stellar-mass surface densities can be recovered well using any of the three data cubes, regardless of the SPS model and prior variations. The new priors then significantly improve the measurements of mass-weighted age and Z compared to results obtained without priors, but they may play an excessive role compared to the data in determining the outcome when no ultraviolet (UV) data is available. Compared to varying the spectral extent of the data cube or including and discarding the additional priors, replacing one SPS model family with the other has little effect on the results. The spatially resolved SED fitting method is powerful for mapping the stellar population properties of many galaxies with the current abundance of high-quality imaging data. Our study re-emphasizes the gain added by including multi-wavelength data from ancillary surveys and the roles of priors in Bayesian SED fitting. With the Euclid data alone, we will be able to generate complete and deep stellar mass maps of galaxies in the local Universe (z . 0.1), exploiting the telescope’s wide field, near-infrared sensitivity, and high spatial resolution.
Volume: 702
Keywords: galaxies: evolution; galaxies: formation; galaxies: fundamental parameters; galaxies: stellar content; galaxies: structure;
Euclid I. Overview of the Euclid mission
Authors: AREA MIN. 02 - Scienze fisiche; Non assegn; ASTRONOMY & ASTROPHYSICS###0004-6361; FLD-9518-2022; ABB-9156-2021; CGD-2351-2022; EJF-3121-2022; HQD-3085-2023; EJJ-2811-2022; EJI-6443-2022; EJM-8740-2022; JTL-4413-2023; JMF-0642-2023; CEY-5704-2022; EJD-4812-2022; CBW-9165-2022; GMB-3707-2022; NRR-3240-2025; EJV-2058-2022; KLG-9557-2024; CCW-8236-2022; JHB-9875-2023; JZK-7057-2024; EKN-8524-2022; M-4834-2013; HPI-3910-2023; FZO-1254-2022; CBM-5148-2022; ELN-8298-2022; FYJ-4908-2022; JNB-8974-2023; EKO-8371-2022; CDD-9382-2022; HSM-2226-2023; GXI-6108-2022; HTG-7108-2023; MNS-3973-2025; NLD-1441-2025; MBW-8974-2025; MWW-2922-2025; ELE-7094-2022; EMH-3888-2022; LUN-9784-2024; NRE-4878-2025; MJK-3407-2025; MKU-1930-2025; HRF-0089-2023; MYB-1698-2025; EJP-5690-2022; HSL-3945-2023; CDR-2303-2022; ENM-6579-2022; KKX-1153-2024; H-1374-2012; CCI-8559-2022; GPF-5137-2022; ICC-1978-2023; DVO-2403-2022; CEY-5520-2022; LXB-7798-2024; GBU-9674-2022; JYY-9592-2024; GAF-9076-2022; N-7472-2018; HPI-5715-2023; GMC-5713-2022; CET-2621-2022; CCQ-1808-2022; HZQ-9553-2023; CEU-2310-2022; EKA-7986-2022; IYE-9818-2023; EKS-5104-2022; CEX-0810-2022; CDP-1330-2022; ENB-4426-2022; IUT-7926-2023; NRF-8920-2025; CFX-9814-2022; MNO-9855-2025; ELT-8576-2022; GWF-4497-2022; LRW-4798-2024; NPR-6255-2025; LXX-3952-2024; IUQ-9509-2023; CEM-2577-2022; AAG-2324-2020; CGF-9764-2022; MNR-3415-2025; FZV-5603-2022; CDP-6815-2022; CEB-5555-2022; EML-3726-2022; EKL-5400-2022; HJF-3296-2022; HQQ-1196-2023; CGJ-4278-2022; GNJ-2760-2022; EKW-9241-2022; IBL-1815-2023; IBE-5307-2023; MJX-3374-2025; CFL-2667-2022; EQG-0473-2022; MOE-9658-2025; CGH-8811-2022; EOA-9903-2022; JHC-4470-2023; F-3305-2011; NRQ-9110-2025; JAL-4401-2023; MGX-9029-2025; ADL-2084-2022; HNI-9120-2023; MXO-2726-2025; CGQ-7607-2022; HIV-4758-2022; H-2445-2014; CHK-6722-2022; EKV-4052-2022; CFS-4854-2022; HQD-7277-2023; ENE-3351-2022; HZW-5449-2023; EMQ-6210-2022; DXP-4308-2022; CHO-3061-2022; CGE-2377-2022; DVF-6208-2022; EOE-6462-2022; HUA-1183-2023; GAQ-4245-2022; B-3004-2019; EMQ-1159-2022; MWB-2657-2025; OGI-4954-2025; CFJ-9437-2022; MDB-9465-2025; ENI-0520-2022; CGD-4757-2022; NLL-4331-2025; CHQ-7334-2022; IUT-7887-2023; HIK-2775-2022; CID-2721-2022; MKL-0317-2025; HRV-6262-2023; NLX-1620-2025; HPR-3987-2023; EPD-2609-2022; CIN-6298-2022; JWI-9457-2024; ABA-4003-2021; LUN-9319-2024; CHT-6086-2022; CJJ-6301-2022; EPI-5877-2022; EQN-6282-2022; EQP-3778-2022; MLC-7865-2025; CGS-7946-2022; HUJ-8209-2023; CJO-3675-2022; CIT-6707-2022; IJL-8365-2023; KBV-9584-2024; MNX-6241-2025; IXG-0675-2023; EPI-1133-2022; MIW-5886-2025; ERP-8410-2022; CJD-7824-2022; CJW-4534-2022; LWL-2178-2024; JNZ-6253-2023; HRE-7633-2023; LHN-5965-2024; NBR-1340-2025; DVP-6438-2022; MTV-3745-2025; GBB-5111-2022; CJL-9982-2022; ENM-3795-2022; HFL-6092-2022; JWS-5245-2024; HRE-8369-2023; HZX-4069-2023; DWH-1491-2022; EMF-2271-2022; E-2727-2014; DUM-7421-2022; KHM-6475-2024; DWB-9873-2022; CIK-7846-2022; CLB-9479-2022; CIE-6835-2022; L-2688-2014; L-8237-2014; EPD-5284-2022; DVO-2795-2022; IVA-7236-2023; NRK-6013-2025; EOI-0533-2022; CHG-4764-2022; MEO-0896-2025; LYP-7992-2024; CHR-0412-2022; EOT-6703-2022; E-8021-2017; JQP-7135-2023; KJE-8808-2024; KYS-9953-2024; JUX-7553-2023; JVP-6988-2024; GAZ-5750-2022; B-4650-2017; EPM-6630-2022; HOH-0341-2023; NQF-1006-2025; JWS-0195-2024; DVH-2646-2022; KJF-0900-2024; EOF-2733-2022; NRQ-0747-2025; CLP-7850-2022; MNQ-9261-2025; EQD-4594-2022; HZM-8546-2023; MJA-0665-2025; HRQ-5543-2023; CJX-1459-2022; EQS-7065-2022; CKU-5761-2022; ERW-9883-2022; CMC-5621-2022; IZK-2114-2023; NKQ-9740-2025; JWR-0207-2024; MGK-5739-2025; ICT-4902-2023; LCD-9664-2024; DXZ-7810-2022; CKL-7062-2022; HTG-8587-2023; MLI-4163-2025; F-6046-2011; JQX-6729-2023; H-8587-2015; KSV-9993-2024; B-4348-2013; MLE-5291-2025; LXC-9468-2024; DVC-6323-2022; ISJ-4889-2023; NHE-3385-2025; FYI-9892-2022; HYQ-1890-2023; GLO-1082-2022; CLB-6565-2022; ODZ-2315-2025; LXG-4348-2024; HVQ-9779-2023; CLA-2403-2022; LEQ-1557-2024; IEY-9629-2023; AGZ-3259-2022; ESE-6413-2022; JCA-1448-2023; LTK-6691-2024; NRV-1756-2025; HSS-3921-2023; NKT-5952-2025; CKY-7280-2022; LAE-7227-2024; ERM-9777-2022; CLE-8094-2022; EQT-2114-2022; DWB-0787-2022; MOF-3949-2025; KHG-8956-2024; IWE-7656-2023; LEM-6307-2024; LGD-0576-2024; NRV-4670-2025; ISE-4850-2023; NRP-9827-2025; HSG-9203-2023; HWT-1959-2023; EQK-0659-2022; MJR-9478-2025; A-2693-2010; NRK-1708-2025; MDM-1195-2025; CNN-3877-2022; MJA-8742-2025; HTC-1442-2023; LFP-0543-2024; KCM-7785-2024; CNB-0840-2022; NNH-4042-2025; EVT-3533-2022; NBV-0138-2025; CMB-5148-2022; DWD-3045-2022; CLS-1691-2022; CNO-7574-2022; ETI-2389-2022; MUJ-4019-2025; CNE-2384-2022; NAR-0759-2025; HSZ-8850-2023; JBC-1940-2023; MUU-5913-2025; JQR-6237-2023; AAR-2500-2020; JCH-7186-2023; MJF-0435-2025; OET-0440-2025; CNV-1364-2022; HNL-2756-2023; JHG-8097-2023; ETR-0407-2022; NHM-2354-2025; I-2511-2015; CMV-6954-2022; HLX-2021-2023; EVU-8943-2022; KBZ-1983-2024; CMV-0535-2022; EUU-7571-2022; IDQ-0489-2023; Y-9126-2019; EST-6854-2022; CPS-0405-2022; HUU-7314-2023; NRQ-2991-2025; CNI-1622-2022; LHX-6504-2024; EUO-2530-2022; DWO-2405-2022; EUJ-0747-2022; HUC-7231-2023; JLH-0562-2023; LZM-1403-2025; EUK-3820-2022; EUP-3029-2022; CPJ-9256-2022; MPH-8187-2025; EVA-7948-2022; CNP-7538-2022; MUR-5952-2025; CPQ-6674-2022; AAB-4141-2020; CNJ-2437-2022; MOI-7902-2025; GCM-4570-2022; JUD-9825-2023; ETR-9956-2022; CDE-1189-2022; JTL-0752-2023; FYJ-6157-2022; EVA-1435-2022; JOH-3745-2023; LNV-3966-2024; DWW-0065-2022; HPK-1894-2023; NRC-3253-2025; GDW-5627-2022; JRB-6526-2023; JUD-5049-2023; MOU-4416-2025; IBV-9243-2023; JJU-8538-2023; EVW-7270-2022; EUR-3435-2022; EZB-5943-2022; MZH-2579-2025; ETN-0093-2022; MLN-7208-2025; KSN-3481-2024; CQF-5798-2022; KAK-0357-2024; NRH-1046-2025; HQG-1163-2023; ODV-6417-2025; EUJ-7842-2022; CQF-9451-2022; NRN-3079-2025; CPJ-5952-2022; NRV-1305-2025; HPJ-9215-2023; MJH-4611-2025; EYU-4413-2022; HQN-4024-2023; CQL-6664-2022; CQN-5681-2022; CPO-8263-2022; EVA-4097-2022; ITG-6579-2023; KQX-5688-2024; EUI-3706-2022; NAC-3229-2025; EVH-4654-2022; EUI-6141-2022; Z-3084-2019; NRR-4468-2025; NEY-9864-2025; JLU-6032-2023; KZA-2845-2024; CPP-2309-2022; JWF-2506-2024; CDI-2545-2022; EVC-7104-2022; JUF-9810-2023; AAL-3681-2020; CRZ-8120-2022; NRE-6942-2025; MYV-1006-2025; EZT-7259-2022; CSA-2204-2022; ODW-7069-2025; NRN-0086-2025; GSK-2844-2022; CQL-4862-2022; CSY-1689-2022; MWU-0619-2025; EWC-1530-2022; FWN-7440-2022; MLW-9657-2025; IDG-1087-2023; JXC-8734-2024; MHT-2448-2025; CSH-1681-2022; EXI-9841-2022; CQY-2505-2022; MUO-4676-2025; CQR-5759-2022; MVC-0524-2025; KER-9145-2024; NXC-1097-2025; MWF-0670-2025; ICL-4957-2023; JGR-4365-2023; AAA-9785-2020; KIY-8658-2024; CRD-1248-2022; CRF-3946-2022; AFY-7086-2022; ABB-8257-2020; GBY-6621-2022; KCY-7025-2024; GAX-2002-2022; EWA-5149-2022; CTE-6775-2022; J-1632-2012; MQB-8858-2025; JBC-8829-2023; CSK-3817-2022; JCH-9007-2023; MCZ-5286-2025; NRK-4601-2025; JNT-8006-2023; MEV-2274-2025; CTC-5087-2022; KLF-9653-2024; CSG-7055-2022; CUA-0149-2022; MJO-3087-2025; FBI-2817-2022; MQG-2678-2025; EZH-1360-2022; FCZ-2066-2022; NRQ-4915-2025; NRR-9928-2025; IUR-5258-2023; GBK-2999-2022; HST-6093-2023; FBI-9285-2022; CTE-6491-2022; NIY-2007-2025; CSS-0465-2022; FZK-6500-2022; FBF-5584-2022; JMX-5918-2023; GTG-7507-2022; HQJ-2322-2023; HTH-8470-2023; GFC-5625-2022; JOL-7661-2023; KDQ-3614-2024; CTA-9883-2022; EXX-4126-2022; CTK-3057-2022; CTP-7970-2022; KLP-3493-2024; KGG-1931-2024; JDI-7888-2023; KNK-3731-2024; EYM-5386-2022; HRW-8595-2023; CWB-4290-2022; EXF-2880-2022; FBE-0351-2022; NBT-5940-2025; EZW-5630-2022; CTZ-4163-2022; GBH-2365-2022; NRR-9298-2025; NRK-6634-2025; EYY-4006-2022; ILN-9494-2023; KRH-1914-2024; FBH-9855-2022; JQE-0542-2023; MHS-6760-2025; JEG-8812-2023; LYQ-5466-2024; MNW-1319-2025; GRD-7772-2022; CVM-9293-2022; AAK-4578-2020; HST-5130-2023; NMQ-1781-2025; LYS-9921-2024; CUW-7080-2022; FBX-9828-2022; MTL-9359-2025; MDJ-5344-2025; CWO-3287-2022; ILS-2135-2023; HSK-3386-2023; HPW-2820-2023; CWY-0165-2022; MPD-8237-2025; JML-9573-2023; JKX-6494-2023; B-1966-2015; JYM-2246-2024; FBM-0217-2022; D-5933-2011; NIQ-3499-2025; JWD-0263-2024; FCV-2900-2022; MGT-4091-2025; JZW-8042-2024; HRR-2616-2023; NRS-7976-2025; NRN-3271-2025; JCW-4739-2023; JXC-9786-2024; CWS-7520-2022; CWV-4019-2022; CYQ-0685-2022; FDG-6756-2022; NDB-3420-2025; DYK-3119-2022; MNZ-8396-2025; CZF-1112-2022; FFG-2233-2022; LSJ-9812-2024; FCS-1018-2022; NRR-0017-2025; NRF-9045-2025; HRX-7202-2023; FGD-1080-2022; CYQ-3539-2022; DAZ-7704-2022; Z-4828-2019; HRM-1931-2023; A-7919-2015; DAV-9216-2022; MYL-2765-2025; HGN-2939-2022; CZQ-4310-2022; MXU-8300-2025; IUI-6764-2023; KJS-6941-2024; CZN-8033-2022; NQK-8653-2025; MTY-4531-2025; GMM-4439-2022; NKL-3434-2025; CYT-5449-2022; KNJ-5611-2024; AAF-6025-2021; GWA-7849-2022; KAK-4177-2024; JAI-5774-2023; DCG-5571-2022; FYU-3294-2022; G-9631-2012; FFY-6602-2022; FIF-2657-2022; JPY-8767-2023; NIN-1609-2025; FIK-3831-2022; J-8907-2012; MDB-8943-2025; JGX-3888-2023; DBQ-1340-2022; FIF-1822-2022; FGP-4216-2022; JGY-3165-2023; HSU-3428-2023; HPY-6920-2023; NEZ-3286-2025; HTZ-8133-2023; DCR-4002-2022; MEV-5100-2025; HWZ-9076-2023; FIK-7572-2022; N-2429-2017; JNC-9013-2023; FIV-8514-2022; Q-5758-2017; FFN-8027-2022; DVM-3899-2022; NRJ-9083-2025; GYG-7175-2022; HYU-3434-2023; DCT-5227-2022; FJF-4165-2022; MDM-2414-2025; LYD-9061-2024; NRF-6534-2025; NPX-1842-2025; DBO-1835-2022; FJT-8530-2022; AAV-9023-2021; DBI-3005-2022; MMS-5823-2025; NAU-8484-2025; GAV-5026-2022; LYK-3518-2024; DDB-6234-2022; HYH-6107-2023; A-2699-2012; NRG-6873-2025; KEL-4830-2024; FNN-4043-2022; MDN-2641-2025; LWS-5330-2024; NRS-6675-2025; NLE-8119-2025; FIV-3763-2022; A-2664-2019; FIQ-7669-2022; MHM-6337-2025; DEC-2913-2022; LBZ-7918-2024; DCP-5865-2022; HQS-3374-2023; FII-8063-2022; KCR-4488-2024; DDY-1012-2022; DDX-0583-2022; HFG-2597-2022; IMW-2405-2023; LFX-5249-2024; GQU-8893-2022; KND-8351-2024; DFA-0403-2022; DVI-9193-2022; MOV-6335-2025; IMM-0353-2023; MPQ-9451-2025; FLK-4707-2022; HLM-5105-2023; MTO-5925-2025; FJK-3463-2022; Q-4575-2017; JCQ-0002-2023; IES-5642-2023; MDZ-3436-2025; FHL-5547-2022; DWN-4354-2022; DWZ-6747-2022; NRP-0502-2025; KEZ-0532-2024; GDK-6541-2022; HUJ-7899-2023; GBI-4899-2022; MXA-3751-2025; DFQ-7859-2022; IVG-8235-2023; ITP-6249-2023; DFY-8508-2022; DVE-7652-2022; FMC-3868-2022; FJJ-3655-2022; JHF-8266-2023; GNV-2271-2022; JHX-6515-2023; MVK-6229-2025; MWK-2416-2025; NRF-5521-2025; MVA-1492-2025; HFG-7438-2022; KNZ-0005-2024; D-1300-2016; IUI-2505-2023; HPN-9567-2023; HXW-4678-2023; DGC-7489-2022; GBF-5775-2022; FJX-8996-2022; MKJ-0611-2025; DFZ-7309-2022; NRU-0154-2025; HVT-6155-2023; AAA-1489-2019; NBX-2664-2025; DGJ-6322-2022; MDD-7519-2025; GNG-7078-2022; KJS-1644-2024; FNC-4379-2022; DFC-8070-2022; DII-6557-2022; JMA-2509-2023; MXQ-8599-2025; HRS-2811-2023; MWC-3186-2025; HMK-3035-2023; DHS-8142-2022; D-1237-2017; KEK-6332-2024; MRN-9860-2025; IWF-0425-2023; NRQ-9955-2025; FMN-9310-2022; KNO-5341-2024; D-2437-2012; DXV-8969-2022; FMT-8159-2022; DHH-6443-2022; DYJ-3666-2022; HLL-5972-2023; HLL-6309-2023; GXE-4405-2022; FQI-9285-2022; DVX-6694-2022; KJY-7272-2024; JHX-6642-2023; GCF-0434-2022; FNU-9642-2022; A-4353-2011; DIC-9742-2022; DIQ-9971-2022; FOW-5617-2022; GFU-8637-2022; DJD-5051-2022; F-3052-2014; IRO-7983-2023; NRC-8224-2025; KSI-9422-2024; HSQ-1225-2023; NLM-4855-2025; IMH-2807-2023; FSF-3897-2022; ITX-8160-2023; MYS-2354-2025; HSY-8397-2023; LUL-9658-2024; DKR-3047-2022; HVM-5324-2023; DKO-3585-2022; MDA-3054-2025; NRG-1953-2025; DJO-8166-2022; FZX-4882-2022; JWR-5706-2024; NLF-5244-2025; HQV-1445-2023; MNN-0179-2025; HRN-5646-2023; NQK-3445-2025; FTW-0640-2022; DJN-3869-2022; KZF-8490-2024; FNW-0431-2022; MBT-8435-2025; FOS-7937-2022; LXV-7382-2024; JAO-7873-2023; ABA-3428-2020; DLM-9200-2022; MYA-0386-2025; IGV-6651-2023; AFN-4775-2022; FTY-8452-2022; GZD-9043-2022; IFK-3302-2023; DJX-2897-2022; HQS-3256-2023; GDL-7739-2022; DKG-0898-2022; HRH-6112-2023; GCM-7974-2022; DKF-4281-2022; DLU-8112-2022; HKO-2302-2023; DLP-9078-2022; IWG-2396-2023; HTJ-4919-2023; DLB-8458-2022; MQI-8881-2025; JHP-1576-2023; GSC-5225-2022; JVJ-0877-2024; IFM-0779-2023; IXM-0724-2023; HMZ-6395-2023; DKH-9248-2022; IHG-7220-2023; LZJ-8709-2025; DKA-5086-2022; HRS-4550-2023; IXU-1248-2023; MKP-3087-2025; DNA-3793-2022; GCU-3410-2022; IOF-6591-2023; DLB-6897-2022; DNL-3219-2022; FPR-3817-2022; AAA-6117-2020; HZS-7341-2023; AGE-0251-2022; HTM-1531-2023; EAA-9698-2022; DZO-2834-2022; KBT-5668-2024; KRL-0334-2024; MQC-5441-2025; DNN-3533-2022; DKX-5481-2022; DNY-7864-2022; IOY-7230-2023; HOK-2124-2023; DMR-6962-2022; MTQ-2344-2025; IFV-8400-2023; DXB-7503-2022; KNM-1316-2024; KSG-5747-2024; IVG-7504-2023; FTV-6637-2022; FSY-2184-2022; GGM-6223-2022; DNI-8823-2022; DMX-5934-2022; MVC-4382-2025; MRE-1110-2025; JCV-3612-2023; MST-2965-2025; MRW-3611-2025; KPF-2019-2024; NDK-0885-2025; HPO-8234-2023; IAH-4272-2023; FSG-6281-2022; DMI-3454-2022; FTR-6470-2022; LFC-7290-2024; DMD-3023-2022; MQV-6996-2025; FSO-8783-2022; KCW-5804-2024; MKU-3938-2025; IAF-7465-2023; MDF-9976-2025; LSP-5837-2024; DOA-5683-2022; DNY-0415-2022; DMI-7584-2022; IRP-1078-2023; FUH-9925-2022; NRP-1035-2025; HTE-6970-2023; KQW-8294-2024; GEF-7978-2022; CDP-4089-2022; DQB-9835-2022; JMR-9144-2023; GCQ-0851-2022; HQU-3434-2023; HRX-2781-2023; NRU-8946-2025; DMK-3227-2022; FSF-9689-2022; GCU-4080-2022; DNX-4243-2022; NRR-2948-2025; HEL-3409-2022; FSR-7582-2022; DNY-1328-2022; DWR-3357-2022; DNV-0835-2022; DWT-7233-2022; DPR-5415-2022; GZX-3937-2022; LJL-6604-2024; GCB-0930-2022; MNC-6953-2025; AAV-1857-2021; MVR-8365-2025; INQ-1213-2023; MXB-9468-2025; HPR-0960-2023; FVF-5606-2022; HTK-0092-2023; MDM-6969-2025; MZD-7939-2025; LYL-7929-2024; FVI-7225-2022; R-9864-2019; DPV-0687-2022; HVK-7100-2023; HUZ-7198-2023; IHL-1858-2023; CJV-1729-2022; NRH-6805-2025; IGN-7320-2023; MWU-5876-2025; GEH-7593-2022; JVJ-6571-2024; KKM-4015-2024; HWH-2286-2023; HIF-4249-2022; MUA-9482-2025; FSR-8046-2022; FXG-6905-2022; NVH-1944-2025; FVQ-4930-2022; HFW-5845-2022; MWU-0013-2025; HQL-1128-2023; DYT-3191-2022; NAO-9053-2025; CDE-5677-2022; FYD-1647-2022; LQG-0636-2024; FWJ-9813-2022; DOX-4367-2022; MDQ-9712-2025; DRO-1214-2022; IRI-1547-2023; AAY-7554-2020; DRA-2090-2022; GYJ-2164-2022; NDD-4439-2025; FSV-8899-2022; KLA-7316-2024; MSO-9043-2025; NRQ-6647-2025; NBF-7788-2025; NRJ-0532-2025; DPD-7597-2022; GEQ-9811-2022; JWG-7083-2024; HYZ-8827-2023; JLJ-3892-2023; JUW-8998-2023; NRU-6306-2025; KKU-1164-2024; NGW-4569-2025; NRN-5390-2025; FVK-3262-2022; IZJ-2041-2023; IZM-5556-2023; GBY-3944-2022; DZW-2293-2022; FZC-0117-2022; FVQ-3296-2022; DQK-6454-2022; INY-7970-2023; JMS-1539-2023; IHY-7449-2023; DQG-9931-2022; MUY-9401-2025; N-7309-2013; IOB-3689-2023; NKZ-4607-2025; KKA-8210-2024; FXL-6886-2022; MVM-9062-2025; GAI-0880-2022; HZG-0455-2023; HRO-4465-2023; KKE-9686-2024; IPT-3669-2023; DSO-0650-2022; IUS-5192-2023; FXZ-9990-2022; FXE-2183-2022; MLB-4828-2025; IQA-1300-2023; GBU-9294-2022; FYQ-2273-2022; GBG-8291-2022; MYI-9415-2025; HQO-2360-2023; LRA-7407-2024; JAN-6167-2023; HSW-9999-2023; DXK-9781-2022; 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Journal: ASTRONOMY & ASTROPHYSICS
Published: 2025
DOI: 10.1051/0004-6361/202450810
The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015–2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14 000 deg2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance.
Volume: 697
Keywords: cosmology: observations; instrumentation: detectors; instrumentation: spectrographs; space vehicles: instruments; surveys; telescopes;
ECMR 2025 Cover Page
Authors: Gasteratos Antonios; Bellotto Nicola; Tortora Stefano
Journal: 21101337815
Published: 2025
Ecofriendly Synthesis of Titanium Dioxide for Glyphosate Adsorption
Authors: Marconi Eleonora; Lopez Alberto; Bertela Federica; Meneghini Carlo; Battocchio Chiara; Gattia Daniele Mirabile; Vanga Giuseppina; Centomo Paolo; Zecca Marco; Rizzotto Valentina; Pettenuzzo Silvia; Roverso Marco; Bogialli Sara; Simon Ulrich; Chen Peirong; Tortora Luca; Bertelà Federica; Mirabile Gattia Daniele
Journal: EUROPEAN JOURNAL OF INORGANIC CHEMISTRY
Published: 2025
The widespread use of glyphosate for weed control in agricultural, silvicultural, and urban areas worldwide is causing concerns about its potential toxicity and mobility in environment. Consequently, there is a pressing need to develop treatment processes to mitigate the effects of glyphosate, its metabolites, and/or coadjutants on the environment. Titanium dioxide nanoparticles (TNPs), among the most widely used engineered NPs, have recently attracted significant attention for glyphosate adsorption. In this study, TNPs were obtained through two synthesis procedures working at low temperatures and with a reduced amount of organic solvent. The first involves a polycondensation reaction of alkoxide precursors at 70 °C in a water-in-oil (W/O) microemulsion with a 1 : 1 volume ratio, employing cetylpyridinium bromide (CPB) as a cationic surfactant to obtain crystalline TNPs. In the second method, two resins characterized by different morphologies were used as a template, to grow amorphous TNPs. Glyphosate adsorption tests performed at different pH values, i.e. 4.0 and 8.5, revealed that the analyte is more effectively retained by the TNPs at pH 4.0, at which TiO2 surfaces are positively charged and better interact with anionic glyphosate species. TNPs obtained via microemulsion using titanium alkoxide as the precursor and calcined at 450 °C showed excellent performance, removing from the solution nearly 99% of glyphosate, even at pH 8.5. Similarly, resin composites work efficiently in eliminating a high percentage of glyphosate, taking advantage of a better dispersion of amorphous TiO2 and a higher surface-to-volume ratio. This study demonstrates the effective capture of glyphosate by titanium dioxide nanoparticles, highlighting some factors contributing to the adsorption ability, and their potential as a unique tool for adsorbing glyphosate in a one-pot process.
Volume: 28
Keywords: adsorption; glyphosate; nanoparticle; polymerization; titanium dioxide;
Euclid: Early Release Observations – The surface brightness and colour profiles of the far outskirts of galaxies in the Perseus cluster
Authors: AREA MIN. 02 - Scienze fisiche; ASTRONOMY & ASTROPHYSICS###0004-6361; MDH-6494-2025; CFE-6365-2022; DWB-0787-2022; FYQ-3698-2022; NAA-8765-2025; HZW-5449-2023; GBG-8291-2022; DXA-1243-2022; FZK-6500-2022; DVE-7652-2022; GBG-9412-2022; H-2913-2012; K-9464-2019; H-4394-2019; MQV-6996-2025; OVM-5938-2025; JYY-9592-2024; OAA-4277-2025; HRO-8503-2023; Z-4828-2019; EJM-8740-2022; FZO-1254-2022; FYJ-9637-2022; CEY-5520-2022; EKA-7986-2022; IUT-7926-2023; IUQ-9509-2023; AAO-6325-2021; L-8385-2017; JWI-9457-2024; LUN-9319-2024; HFL-6092-2022; E-2727-2014; IVA-4275-2023; EOV-3838-2022; B-4650-2017; IRQ-6937-2023; H-8587-2015; B-4348-2013; DVC-6323-2022; NHE-3385-2025; LEQ-1557-2024; AGZ-3259-2022; NKT-5952-2025; CNE-2384-2022; EUK-3820-2022; HPK-1894-2023; CPC-6980-2022; IBV-9243-2023; CQF-5798-2022; KLD-3528-2024; CQR-5759-2022; DWK-1716-2022; CSK-3817-2022; FBF-5584-2022; FBE-0351-2022; CTZ-4163-2022; GBH-2365-2022; DWQ-9372-2022; FBM-0217-2022; DWS-1040-2022; DXH-0671-2022; GEK-4486-2022; CYT-5449-2022; GWA-7849-2022; B-8502-2016; Q-5758-2017; GFM-0308-2022; A-2699-2012; GAU-7672-2022; FIV-3763-2022; FLK-4707-2022; MTO-5925-2025; DWZ-6747-2022; HUJ-7899-2023; DFQ-7859-2022; V-6916-2017; GNG-7078-2022; FLD-9518-2022; DVP-3997-2022; KEK-6332-2024; DWT-4779-2022; HXJ-7641-2023; DKF-4281-2022; DWD-4131-2022; DLB-6897-2022; HTM-1531-2023; GBD-7573-2022; MTQ-2344-2025; FSY-2184-2022; DMX-5934-2022; ABC-8644-2021; K-4114-2015; DNW-6364-2022; DXL-4304-2022; DXO-8435-2022; NKY-6871-2025; IZJ-2041-2023; GWX-9207-2022; OWM-0849-2025; LGB-5701-2024; GDK-6495-2022; T-7378-2018; AAB-2503-2019; GCB-5227-2022; OAE-4195-2025; GCA-5567-2022; NZU-7226-2025; NHV-9369-2025; DZE-1995-2022; O-9396-2015; DTO-7937-2022; P-2194-2018; 59165454500; 6603023234; 7003267532; 55505051100; 57206423651; 6602409206; 55365150900; 57192921002; 8970939400; 35494536400; 8833942000; 10738797800; 36195346900; 55929371000; 58303888900; 57206536839; 56261663500; 57204700965; 58114843000; 7005317106; 6701390827; 14629998500; 56176939800; 57220414927; 6505819655; 57225389323; 35421870300; 7004185737; 6701447926; 7004168457; 7004279376; 56592859600; 8316050500; 24439181000; 55948641800; 54924573500; 56260193000; 37121732700; 7003910265; 6507398813; 55757270100; 8856476200; 59636105400; 7004529134; 6602521535; 6601991850; 24461026200; 56181792800; 24587025200; 9639653200; 36627225700; 36657273100; 8527480900; 14008117700; 6603519641; 7202555066; 16024707000; 6603380199; 55539553700; 35425530800; 55885669700; 35227493200; 6701865592; 55578049300; 56216916000; 6603602446; 56149076900; 6603205767; 6603770482; 56403356600; 36195926600; 14058603600; 10239419900; 14025617800; 57815020000; 6506385309; 56463558800; 14056466700; 55665939900; 14832846900; 7004208543; 7004629002; 14050522100; 58095754900; 55913343900; 57544565000; 7003604949; 57203250534; 15770290900; 57190439701; 7006538931; 8842216700; 55337191500; 57225899623; 57190443165; 7004160690; 57218941481; 14063887300; 55845420026; 6602208520; 58502049600; 58937209900; 17436196900; 57203391123; 57191960842; 6602565951; 57191419742; 59730206000; 7101771030; 7005350024; 9333441800; 6603819488; 56512377200
Journal: ASTRONOMY & ASTROPHYSICS
Published: 2025
DOI: 10.1051/0004-6361/202554838
The Perseus field captured by Euclid as part of its Early Release Observations provides a unique opportunity to study cluster environment ranging from outskirts to dense regions. Leveraging unprecedented optical and near-infrared depths, we investigate the stellar structure of massive disc galaxies in this field. This study focuses on outer disc profiles, including simple exponential (Type I), down-bending break (Type II) and up-bending break (Type III) profiles, and their associated colour gradients, to trace late assembly processes across various environments. Type II profiles, though relatively rare in high dense environments, appear stabilised by internal mechanisms like bars and resonances, even within dense cluster cores. Simulations suggest that in dense environments, Type II profiles tend to evolve into Type I profiles over time. Type III profiles often exhibit small colour gradients beyond the break, hinting at older stellar populations, potentially due to radial migration or accretion events. We analyse correlations between galaxy mass, morphology, and profile types. Mass distributions show weak trends of decreasing mass from the centre to the outskirts of the Perseus cluster. Type III profiles become more prevalent, while Type I profiles decrease in lower-mass galaxies with cluster centric distance. Type I profiles dominate in spiral galaxies, while Type III profiles are more common in S0 galaxies. Type II profiles are consistently observed across all morphological types. While the limited sample size restricts statistical power, our findings shed light on the mechanisms shaping galaxy profiles in cluster environments. Future work should extend observations to the cluster outskirts to enhance statistical significance and explore looser environments. Additionally, 3D velocity maps are needed to achieve a non-projected view of galaxy positions, offering deeper insights into spatial distribution and dynamics.
Volume: 699
Keywords: galaxies: clusters: individual: Perseus; galaxies: evolution; galaxies: interactions; Galaxy: disk;
The Hera Space Mission in the Context of Small Near-Earth Asteroid Missions in the Past, Present and Future
Authors: Michel Patrick; Küppers Michael; Fitzsimmons Alan; Green Simon; Lazzarin Monica; Ulamec Stephan; Abell Paul; Sugita Seiji; Campo Bagatin Adriano; Carry Benoit; Charnoz Sébastien; de León Julia; Ferrari Fabio; Hérique Alain; Jutzi Martin; Karatekin Özgür; Kohout Tomas; Murdoch Naomi; Okada Tatsuaki; Palomba Ernesto; Pravec Petr; Raducan Sabina; Snodgrass Colin; Tortora Paolo; Vincent Jean-Baptiste; Wünnemann Kai
Journal: 28261
Published: 2025
DOI: 10.1007/s11214-025-01195-1
The Hera mission of the European Space Agency was launched successfully on October 7, 2024 and will perform the first rendezvous with a binary asteroid in fall 2026. It will measure in great detail the characteristics of the binary asteroid (65803) Didymos. This will include for the first time the interior of an asteroid, as well as the outcome of the impact of the NASA DART mission on the small moon, called Dimorphos; of the binary system. The first asteroid deflection test will thus be fully validated, enabling impact model extrapolations to other cases. Hera uses a unique architecture that includes for the first time a main spacecraft and two cubesats for deep space asteroid exploration. It takes place in the context of the golden age of asteroid exploration, with no less than 8 missions in development or already flying to asteroids and great successes of past missions, in particular the two recent asteroid sample return missions OSIRIS-REx by NASA and Hayabusa2 by JAXA. Up to now, all new asteroids visited by a spacecraft have generated great surprises, especially regarding their often counter-intuitive response to external actions, showing that we are still far from fully understanding the properties of these bodies in their low-gravity environment. By investigating and interacting with small asteroids, we should eventually be able to better understand and predict their properties as a function of common characteristics identified by ground-based observations. We are not there yet. In this paper, we present how Hera will contribute to this endeavor.
Volume: 221
Keywords: Asteroids; Binary asteroids; Planetary defense; Space mission;
Long-term effectiveness, safety, and liver stiffness dynamics of PBC treatment with obeticholic acid in real-world
Authors: AREA MIN. 06 - Scienze mediche; ITA; Goal 3: Good health and well-being###25122; EAE-4108-2022; AAB-7965-2019; GXH-0637-2022; ABA-7458-2022; AAM-5199-2020; GYG-3745-2022; DQA-3167-2022; EEZ-3131-2022; DWH-6622-2022; DJL-4541-2022; GDO-6870-2022; EPF-4015-2022; HXI-6162-2023; CER-4322-2022; EPL-8933-2022; CLX-8747-2022; R-6598-2016; CUO-7026-2022; CDG-6373-2022; EAA-0713-2022; CMD-8697-2022; HMC-6765-2023; DWO-5433-2022; EUY-7780-2022; OWZ-9517-2025; GJN-4882-2022; EPQ-0611-2022; CST-5700-2022; DGV-4842-2022; NOF-1514-2025; AAC-1949-2019; AAE-3161-2022; DVV-9362-2022; CFM-6817-2022; ELB-9576-2022; AAA-5759-2019; LFT-8668-2024; GNF-9719-2022; J-8600-2018; CEH-2506-2022; GDY-8839-2022; CGI-5783-2022; J-8463-2018; E-1120-2012; DBM-5248-2022; JHF-5645-2023; NCV-8425-2025; DTY-5484-2022; DXS-4726-2022; OUU-0112-2025; CJX-2082-2022; JCS-8414-2023; EPL-1215-2022; FSR-1611-2022; GVU-0673-2022; DWF-4268-2022; FIH-4311-2022; MUO-3257-2025; DPA-2383-2022; EQL-9934-2022; DQK-8599-2022; GBJ-7157-2022; GDZ-6667-2022; ORW-9434-2025; EQJ-1234-2022; FQB-6797-2022; MQU-5709-2025; K-4255-2019; FLO-9066-2022; ESJ-6426-2022; DKA-8928-2022; J-4394-2019; DZH-2825-2022; EIZ-6768-2022; DGZ-4325-2022; FUU-1830-2022; EMO-8688-2022; GPG-1122-2022; IAZ-8837-2023; AFM-2519-2022; PHG-8971-2026; KJQ-3800-2024; PFZ-5711-2026; GDC-3815-2022; JVS-9756-2024; DPL-3467-2022; CGZ-1469-2022; DTZ-5739-2022; LWM-3292-2024; DPL-0586-2022; GBB-8947-2022; GDJ-0380-2022; CDY-1662-2022; K-7706-2016; JCS-0572-2023; CEV-0715-2022; E-2565-2011; MYM-7264-2025; FQT-1261-2022; CWY-4285-2022; CFF-4678-2022; FZV-1726-2022; MNU-4399-2025; BBE-1333-2022
Journal: JHEP REPORTS
Published: 2025
DOI: 10.1016/j.jhepr.2025.101448
Volume: 7