Dark matter direct detection experiments based on nuclear recoils
LAURA BAUDIS DM UNIVERSITY OF ZURICH
IDMEU KICKOFF MEETING e- MAY 10, 2021 2
STRUCTURE OF THE TALK (AS GIVEN BY ORGANISERS)
▸ Brief overview of the status of direct detection experiments based on nuclear recoils (DDNRs), recalling the basic concepts
▸ Current challenges in DDNRs & cross-talk with others
๏ problems in comparison of results within our community
๏ problems in comparison of results outside our community
๏ are data/results/software tools shared within/outside our community?
▸ Current and future needs
๏ what other inputs could be useful?
๏ what can we offer? 3
STRUCTURE OF THE TALK (AS GIVEN BY ORGANISERS)
▸ Brief overview of the status of direct detection experiments based on nuclear recoils (DDNRs), recalling the basic concepts
▸ Current challenges in DDNRs & cross-talk with others
๏ problems in comparison of results within our community
๏ problems in comparison of results outside our community
๏ are data/results/software tools shared within/outside our community? Disclaimer: personal view, ▸ Current and future needs eld; hopefully relevant not a completef survey of ๏ what other inputs could be useful? the input for discussions! ๏ what can we offer? 4
BASIC CONCEPTS & STATUS OF DDNR EXPERIMENTS
(p) (p') NRs
Look for DM collisions - e Nucleus with nuclei (NRs) e- Interactions with electrons
ERs in the atomic shell (ERs) are (mostly) backgrounds
DM-SM N mediator N (q=p-p')
q
DIRECT DARK MATTER DETECTION VIA NUCLEAR RECOILS
▸ Main physical observable: a differential nuclear recoil spectrum
▸ Its modelling relies on several phenomenological inputs from other felds/communities
Astrophysics: Particle physics: local density, mass, cross v-distribution section
Hadronic/Nuclear physics: structure functions Direct detection 7
DIRECT DETECTION KINEMATICS: PARTICLE MASS
▸ DM particle mass which can be probed with NRs: few GeV to 100 TeV
Dolan, Kahlhöfer, McCabe, ▸ Lower masses (~100 MeV) via, e.g., Migdal effect arXiv:1711.09906 and others
DM 2 v NRs 1 m DM = 2 e- E kin
DM
ERs
e- Figure from T. Lin, TASI lectures on DM models and direct detection, arXiv:1904.07915 8
THE DIFFERENTIAL NUCLEAR RECOIL SPECTRUM
dR ⇢0 1 d 3 2 vmin = mN ER/2µ N = NN vf(~v)d ~v
Detector physics Particle/nuclear physics Astrophysics
N
MWIMP = 100 GeV Xe σWn=1×10-47 cm2
Ge
Ar
Si Spin- independent NR spectrum 9
DIRECT DETECTION: CROSS SECTION VS. PARTICLE MASS
Eth for NRs 10-39 cm2 2 vmin mN ER/(2m ) v E /(2m )
m
Interaction cross section cross Interaction ~ 1/mχ Elastic DM-nuclei Electron collisions recoils
10-51 cm2
1 GeV 1 TeV Mass of dark matter particle MAIN DIRECT DETECTION TECHNIQUES/EXPERIMENTS
Phonons
CaWO4: Ge, Si: CRESST SuperCDMS NaI: EDELWEISS COSINUS
ER
Ar: DEAP-3600 CsI: KIMS C3F8: PICO Ionisation Photons NaI: ANAIS Ge: CDEX DAMA/LIBRA, Si: DAMIC-M, SENSEI COSINE, SABRE Ar, Ne: TREX-DM Xe: LZ, PandaX-4T, XENONnT, DARWIN He:SF6: CYGNUS Ar: DarkSide-50, DarkSide-20k, ARGO Ag, Br, C: NEWSdm 10 11
NR EXPERIMENTS: PAST, PRESENT, FUTURE
Spin-independent cross section upper limits at 60 GeV WIMP mass 10-41cm2 in ~1998 to few x 10-47 cm2 in ~2018
~ now
=
We have come a long way!
Figure: Rick Gaitskell, 2020 12
THE CURRENT NR DIRECT DETECTION LANDSCAPE
100 MeV 1 GeV 1 GeV 1 TeV
PDG 2020 PRL 123, 2019 Ge, Si, CaWO3,… detectors Argon detectors
XENON1T Neutrino Xenon coherent detectors scattering
Scattering off nuclei (Migdal effect, S2 only) Scattering off nuclei, SI 13
THE FUTURE/PROJECTED NR DIRECT DETECTION LANDSCAPE
Bolometers, CCDs,... (plus new technologies)
Noble liquids
Figure: APPEC DM Report, arXiv:2104.07634 14
CURRENT CHALLENGES IN DDNR & CROSS-TALK WITH OTHERS CURRENT CHALLENGES: BROAD OVERVIEW
▸ Combine input from astrophysics, cosmology, particle physics, hadronic & nuclear physics
▸ Account for theoretical and astrophysical uncertainties
▸ Account for experimental uncertainties, in particular also those related to the 'ultimate' neutrino backgrounds
▸ Decide on statistical framework, blinding strategies, etc
▸ Decide on common tools, data sharing & format, documentation
▸ ... 16
ASTROPHYSICS: LOCAL DARK MATTER DENSITY
▸ Local measures: vertical kinematics of stars near Sun as Direct detection rates: ‘tracers’ of the gravitational potential
▸ Global measures: extrapolate the density from Milky Way’s linear dependance on the local density; 3 rotation curve derived from kinematic measurements of "canonical value" is 0.3 GeV/cm gas, stars Range of values in the literature: ~ [0.2 - 0.6] 10 T. Piffl et al. ▸ Major source of uncertainty: contribution of baryons (stars, GeV/cm3 Parameters from Galaxygas, stellar models remnants, …) to the local dynamical mass 3144 T. Piffl et al. The fact that r0,dm changes with ρdm, on account of 0.9 See review by Justin• Read, Journal of Phys. G 41 (2014) ! the halo constraints: setting r0,dm = 20 kpc increases ρdm, For the surface density between 900 pc, we find∝ q−α, α . ! ± =089 by 2%. 0 8 2 !(z 0.9kpc). (69 15) M pc− . Equal scale radii for thin and thick disc: setting
=] = ± ! • 3 Rd,thick/Rd,thin =0.6 (resulting in Rd,thick 2kpc and Below− in Fig. 15, we set these measurements in context with esti- " 0 7 Rd,thin 3.5kpc similar to Bovy et al. (2012)), increases mates from. the literature. " ρdm, by 4%. ! Flattening the dark halo: a flatter dark halo increases [GeV cm 0.6 • 4.3 Other properties ρ significantly. See Fig. 8. dm dm, , ! 0 We nowρ give results for the model with a spherical dark halo. The Systematic uncertainties in the distance scale of J08: if 0.5 • 3 12 this distance scale is increased by a factor α, ρdm, proves to best-fitting model has a virial mass M200 (1.3 0.1) 10 M . ! The above-mentioned systematic uncertainties= ± translate× into! a be almost proportional to α, with a 20% increase in α caus- 0.4 <10 per cent uncertainty0 60 in the70 virial mass,80 but this does91 not encom-0 ing ρdm, to increase by 8%. A different value for the binary . . . . . ! pass the uncertainty introduced byaxis the assumed ratio q shape of the radial fraction has a very similar, but smaller, effect to a general mass profile of the dark matter halo. For the models with flattened change of the distance scale, and is hence also covered in haloes, we find slightly increased virial masses of 1.4 1012 M Figure 8. Best-fitting value for0.89 the local dark-matter3 density this uncertainty. and 1.6% 1012=0M for.0126 the axis ratiosq 0.8 andM 0.6, respectively.pc× !10% ρ DMas a function of the assumed flatting q of the dark-matter Thedm, × total mass! of the⇥ Galaxy’s stellar disc± is halo.! A value of q =1impliesasphericalhalo,whilesmaller2 The two most critical systematic uncertainties are (3.7 1.1)tot(<10010.M9kpc). This = is 69 lower but10 not M farpc from the values lead to oblate configurations. The dashed black line shows therefore the axis ratio q of the dark halo and the distance canonical± value× of 5 !1010 M . It is± within the range of 3.6 scale used to construct the observational vertical stellar den- –5.4apower-lawfittedbyeyetothepoints.1010 M estimated× by! Flynn et al. (2006). Combining the stellar× disc! with the bulge and the gas disc, we arrive at a sity profile. Simply adding in quadrature the uncertainties Figure 12. Upper panel: mass surface densities in our models for the stars total baryonic mass (5.6 1.6) 1010 M , or a baryon fraction otherPif thanf et al, halo MNRAS flattening 445 (2014) listed above leads to a combined M. Cautun et al, MNRAS 494 (2020) 3, using Gaia DR2 (black points and lines) and gas (grey points and lines). The green and orange (4.3age or0.6) chemistry per cent. This (e.g.± value Binney× is much &! Merrifield lower than the 1998), cosmic the minor systematic uncertainty of 10%. Combining this with the diff±erence between the two thin-disc curves in Fig. 7 shouldshaded area show the corresponding one/two sigma∼ regions reported by baryon fraction of 16 per cent (Hinshaw et al. 2013; Planck Col- Flynn et al. (2006uncertainty). Lower panel: associated the ratio F with/F dark-haloof the contributions flattening we arrive not be considered∼ significant at this stage. R,bary R,dm laboration XVI 2013), once again illustrating the ‘missing baryon to the radial forceat our at R0 resultfrom baryons and dark matter. In both panels, the problem’The (e.g. green Klypin error et al. 1999 bars). in While Fig. this 7 show baryon the fraction stellar does densitiesgrey shaded area illustrates the systematic uncertainties of ρ with the α dm, 3 notinferred include bythe massGilmore of the & Galaxy’s Reid (1983) virial-temperature for stars corona, with absolute6 (interpolated) best-fitting value marked(0.48 by theq black− )GeVcm dashed line.! − For this10% ρdm, = × ± (22) the mass of the corona within 20 kpc of the GC is negligible value, we have FR,bary/FR,dm 0.85. α 3 visual magnitude MV between∼ 4 and 5 with an assumed ! ∼ !(0.0126 q− )M pc− 10% (Marinacci et al. 2010); the missing baryons have to lie well outside1 × ! ± vertical metallicity gradient of 0.3dex/ kpc− (in their Ta-galaxies (Bershady et al. 2011;Martinssonetal.2013). It is still the visible Galaxy in the circum- or intergalactic− medium.2 with α =0.89 and q the axis ratio of the dark halo. bleThe 2). thick The disc green contributes dots about in Fig. 32 per6 show cent of the theχ disc’svalues stellar we obtainlower than the value of 0.83 0.04 found by Bovy & Rix (2013). Note, there± is an additional potential source of uncer- masswhen which we is adopt lower thanthe Gilmore–Reidthe 70 per cent found data by points.J08. This They result indicate 2 tainty that we have not included in our estimate: Sch¨onrich depends,adeeperminimumin however, on our decisionχ tooccurring equate the radial at a scalelengths smaller dark-halo 3 5KINEMATICS& Bergemann (2013) find hints that the common practice ofdensity: the two discs.ρdm, If the=0 scalelength.01200 M of thepc− thick. disc is assumed to ! ! be shorter, as found by Bovy et al. (2012a), the mass fraction in this Here, we discussof assuming the kinematic uncorrelated properties of our errors best-fitting in the model. stellar parameters 1 component increases to 60 per cent. The better agreement with The circularwhen speed at deriving the solar radius, distancevc(R0 estimates) 240 km s− isis not largely a good approxima- ∼ = J08 is only apparent, however, because these authors found a longer the result oftion the adopted andleads values of toR over-confident0 8.3 kpc, the proper results. motion Hence of the parallax 4.1 Systematic uncertainties = scale radius for the thick disc. Sgr A*, anduncertaintiesv , the solar motion reported w.r.t. toby the LSR. Binney Our constraints et al. (2014b) might be ! TheFig. 12 resultsshows for presented several fairly above successful are basedspherical on models a very the sophis-for the massunder-estimated. model actually fix the ratio Tov testc(R0) the/R0 (McMillan possible2011 influence). we doubled surfaceticated densities model of the that stellar involves and gaseous a number discs at R0 of(upper assumptions panel) andFor the local escape speed vesc √2#(R0), we find a value the1 individual parallax= uncertainties (a worst case scenario) andapproximations. the ratio of the radial Deviations forces at R0 from of the the baryons truth from and dark these mat- assump-of 613 km s− . Piffl et al. (2014) recently found a lower value of 54 and1 repeated the fit. The best-fitting value for ρdm, in- ter (lower panel). The upper panel shows good agreement with the 533+41 km s− , but for this they used a modified definition of the ! tions and approximations will introduce systematic errors− estimates of the baryonic surface densities derived from Hipparcos escape speedcreased as the minimum by 7%. speed A needed similar to reach uncertainty 3Rvir.Ifwe is shared by all into our results. We can assess the size of such systematic ∼ 1 data by Flynn et al. (2006, coloured bands). The lower panel shows apply their definitionstudies that to our use model distances we find a inferred value of 580 from km stellars− parameters. errors much more easily in some cases than in others. We that equal contributions to the radial force are achieved for local which is still on the high side, but within their 90 per cent confi- have not assessed the errors arising from: dark matter densities ρdm, that are lower than our favoured value dence interval. The uncertainties arising from the above-mentioned ! systematics4.2 on this value Flattening-independent are of order 1 per cent. This comes results mainly for a sphericalthe functional halo, but still form within of the the range mass encompassed model; by the systematic• uncertainties, which is shaded grey. In our best-fitting from our rather strong prior on the mass within 50 kpc and again the functional form of the df; does not coverThe the inverse uncertainties dependence in the dark of matterρdm, profileon q atimplies large that for simi- model,• the solar neighbourhood is mildly dark matter dominated ! the age-velocity dispersion relation in the thin disc;radii.4 lar scale radii r the mass of the dark matter halo within with• only 46 per cent of the radial force coming from gas and stars. 0,dm the adopted value of L0 in disc df: variation will affectThe dataan points oblate in Fig. volume13 show with histograms axis for ratio eachq principalis approximately inde- Alternatively,• we can look at the contribution of disc to the total rotationthe normalisation curve at 2.2 times of the stellar scale halo; radius to check whether our velocitycomponentandspatialbinsdefinedby7.3pendent of q. This is confirmed kpc by< R Fig.< R0 9and (upper panel) that disc is ‘maximal’the power-law according slope to the definition and quasi-isotropy of Sackett (1997 of). We the stellarranges in z thatshows increase the from cumulative bottom to top:mass the distribution upper limits of theas a function of el- find a• ratio V /V 0.63 (V /V 0.72) that is be- bins are at z 0.3, 0.6, 1, 1.5 kpc and the coordinates of each bin’s halo – wec, discwill investigatec, all c, this baryons in ac, all future paper; liptical= radius. low the range of 0.75–0.95= for a maximal disc,= but slightly above barycentre are given at the lower centre of each panel. The vertical the solar motion w.r.t. the LSR. The invariance of the dark matter mass profile can be the typical• range of 0.47 0.08 (0.57 0.07) for external spiral scales of the plots are logarithmic and cover nearly three orders of ± ± qualitatively understood by the following consideration: flat- We have investigated the sensitivity of our results to: magnitude in star density. The plotted velocity components V1 and tening the dark halo at fixed local density reduces its mass
3 R0, which controls the circular speed: a value of R04 = and its contribution to the radial force, KR.But–duetoits We• define the virial mass as the mass interior to the radius R200 that Because of this and also because of the focus of Piffl et al. (2014)onthe 8 kpc reduces ρdm, by 5%. still large thickness – its contribution to the vertical force contains a mean density of 200! times the critical density for a flat universe, fastest stars in the RAVE survey, which carry most of the information on the ρ . The contribution of the gas disc disc to the local bary-escape speed,K wez stillat consider low z theirremains value as almost the more robust constant one. or slightly grows. To crit • onic surface density. If we assume 33% instead of our stan- restore the value of the circular speed at the Sun we have dard value of 25%, we find slightly different structural pa- to either increase the mass of the halo or that of the disc. Downloaded fromMNRAS https://academic.oup.com/mnras/article-abstract/445/3/3133/1052064445, 3133–3151 (2014) rameters for the stellar discs, but our best-fit value for ρdm, However, filling the gap with disc material increases Kz and by guest ! on 29 April 2018remains unchanged. consequently compresses the vertical mass profile predicted Rσ,i for the thin disc: using Rσ,i = 6 kpc reduces ρdm, by the df. Thus the only possibility is to increase the mass • ! by < 2%. of the halo and decrease the mass of the disc in order to
c 2014 RAS, MNRAS 000,1–17 ! 17
ASTROPHYSICS: DARK MATTER VELOCITY DISTRIBUTION
▸ Standard halo model: Maxwellian distribution Necib, Lissanti, Belorukov 2018, Evans, O’Hare, McCabe, (isotropic velocities) PRD99, 2019; Buch, Fan, Leung, PRD101, 2020; and others
2 ⇢(r) r
▸ Recent studies: deviations from SHM, due to SHM anisotropies in the local stellar distribution (in Gaia data)
▸ These arise from accretion events, see, e.g., the “Gaia-sausage” - one of the dominant merger in the solar neighbourhood
▸ Effects for direct detection: escape speed, circular rotation speed; relevant mostly at low Normalised Gaia DM velocity dark matter masses distribution in heliocentric frame 18
COMPARISON WITHIN OUR FIELD: HALO MODEL
Ewans, O'Hare, McCabe PRD 99, 2019, Impact of the halo model on upper limits ▸ Which halo model to use?
๏ As an example, a new SHM, SHM++ proposed in PRD99, 2019: impacts existing upper limits from DDNR experiments
๏ The halo model will infuence the interpretation of results in case of a detection (see, e.g., PRD 102, 2020)
๏ Impact of sub-halos on DDNR results (see Ibarra, Kavanagh, Rappelt, JCAP 12, 2019)
M. Petac, PRD 102, 2020, Reconstruction of DM mass and cross section: (30 GeV, 10-47 cm2; 100 GeV, 5 x 10-47 cm2) 19
PARTICLE PHYSICS: DM MASS AND CROSS SECTION
NRs
Bertone and Tait, Nature 562, 51–56 (2018) 20
PARTICLE PHYSICS: DM MASS AND CROSS SECTION
▸ Popular question: is "the WIMP" dead, and if not, what is the probability that we will fnd or exclude it?
▸ What are plausible cross section targets to guide future detectors?
Hisano, Ishowata, Hagata, JHEP 06 (2015), NLO Wino- nucleon cross section Wino 47 2
L.Roszkowski, January 2020
47 2
m
HADRONIC/NUCLEAR PHYSICS: STRUCTURE FUNCTIONS
▸ Recently, two approaches to organise WIMP-nucleus interactions
๏ NREFT: one-body operators (all d.o.f integrated out but nucleons and WIMPs)
๏ ChEFT: including couplings to two nucleons (such as WIMP-pion coupling) + large-shell model many-body calculations (pions, nucleons and WIMPs as d.o.f)
๏
see: M. Hoferichter, PHYSTAT Dark Matter 2019 22
HADRONIC/NUCLEAR PHYSICS: STRUCTURE FUNCTIONS
▸ Recently, two approaches to organise WIMP-nucleus interactions
๏ NREFT: one-body operators (all d.o.f integrated out but nucleons and WIMPs)
๏ ChEFT: including couplings to two nucleons (such as WIMP-pion coupling) + large-shell model many-body calculations (pions, nucleons and WIMPs as d.o.f)
๏ Figures: full set of coherent contributions
Hoferichter, Klos, Menendez, Schwenk, Phys.Rev. D99 (2019) - ChEFT + shell model
Software package: ChiralEFT4DM, Python package: https://theorie.ikp.physik.tu-darmstadt.de/strongint/ ChiralEFT4DM.html 23
BACKGROUNDS: THE NEUTRINO FOG C. A. J. O'Hare PRD 102, 2020
▸ Sensitivity of DDNR experiments: eventually limited by the neutrino backgrounds
▸ Discovery of a signal: only possible if excess in events > stat. fuctuations in the background
▸ The "neutrino fog" depends on
๏ systematic uncertainty in neutrino fuxes (~2% in 8B, ~20% for atmospheric neutrinos)
๏ nuclear and astro inputs for the DM signal
C. A. J. O'Hare PRD 94, 2016
Neutrino "foor" for 3 sets of 1-σ uncertainties on the Discovery limit of a 5 TeV WIMP in an local density, speed and argon target, as a function of the atm. escape velocity for a neutrino event N and fract. uncertainty xenon target on the atm ν fux: δΦatm/Φatm 24
BACKGROUNDS: THE NEUTRINO FOG
Upper limits, 100 t x y and 1000 t y 5σ discovery for 6 x 10-49 cm2, 50 GeV, exposure in Xe target 1000 t x y exposure in Xe target
Figures: Knut Moraa Shaded grey areas: the “neutrino fog” -> the lightest area shows the WIMP cross-section where more than 1 ν event is expected in the 50% most signal-like (S1, S2) region; subsequent shaded areas: 10-fold increases of the ν expectation 25
COMPARISON WITHIN OUR FIELD: STATISTICAL FRAMEWORK
▸ So far: no consensus on the statistical inference of DDNR data, different approaches used by various collaboration (see, e.g., talks at PHYSTAT-DM 2019 https:// indico.cern.ch/event/769726/overview)
▸ New White Paper (arXiv: 2105.00599, emerged out of PHYSTAT-DM 2019): to establish set of recommended conventions for reporting results
๏ e.g., profle likelihood-based test statistics -> Likelihood Ratio (PLR) (following Cowan, Cranmer, Gross, Vitells, EPJ-C 71, 2011)
๏ to asses discovery signifcance & construct confdence intervals
▸ See White Paper for full list of recommendations (also on astrophysical parameters & astrophysical neutrinos) 26
COMPARISON WITHIN OUR FIELD: DATA SHARING
▸ Data sharing: non-uniform in terms of content, location, format (Zenodo, GitHub, ancillary fles on arXiv, ...)
▸ Examples:
๏ CRESST-III data description, arXiv:1905.07335
๏ XENON1T S2-only data: https://doi.org/ 10.5281/zenodo.3982637 and https:// github.com/XENON1T/s2only_data_release
๏ SuperCDMS, arXiv:2005.14067, ancillary fles
▸ Challenge: good documentation of released data 27
COMPARISON WITHIN OUR FIELD: SOFTWARE TOOLS
▸ Software tools:
๏ NEST (GitHub, Zenodo)
๏ Various public analysis tool on GitHub (data management, streaming analysis for xenon experiments: Strax/Straxen)
๏ Dark matter limit plotter: https:// supercdms.slac.stanford.edu/dark-matter-limit-plotter
๏ Other?
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COMPARISON WITH OTHER FIELDS: SOFTWARE TOOLS
▸ How to compare the data reliably with accelerator searches and indirect detection?
๏ Simplifed models; EFTs; UV complete models?
▸ How to make the underlying assumptions transparent?
▸ Which halo model, including new velocity substructures as revealed by Gaia data?
▸ Software examples (see also C. Arina, Review on Dark Matter Tools, arXiv: 2012.09462):
๏ DarkSUSY 6, An Advanced Tool to Compute Dark Matter Properties Numerically, https://darksusy.hepforge.org (JCAP 1807, 2018)
๏ DarkBit, a GAMBIT module for computing dark matter observables and likelihoods (EPJ-C 77, 2017)
๏ MicrOMEGAs (https://lapth.cnrs.fr/micromegas/), Recasting DD limits (EPJ-C 81, 2021) 29
COMPARISON WITH OTHER FIELDS: EXAMPLE
▸ Is Mirac-Less WIMP dark matter (abundance not set by freeze out during a standard cosmology) ruled out? Jason Arakawa, Tim Tait, arXiv:2101.11031
100 MeV 10 TeV EW triplet scalar feld
LHC XENON1T
FERMI HESS Planck CMB
FERMI HESS DD constraints depend Planck CMB of λeff (effective coupling through Higgs exchange) 30
CURRENT AND FUTURE NEEDS OF DDNR COMMUNITY 31
CURRENT AND FUTURE NEEDS OF DDNR COMMUNITY
▸ Within the community
๏ agree on astrophysical, hadronic & nuclear physics input
๏ agree on treatment of uncertainties and statistical framework (perhaps also on blinding strategies?)
๏ agree on common/public software tools & data sharing (publish likelihoods?)
๏ discuss combined analyses (where applicable)
▸ Interfaces with other communities
๏ public tools to model experimental parameters and uncertainties
๏ what are the best/most up-to-date tools to combine data from DD, ID, cosmology, accelerators?
๏ other? 32
Looking forward to fruitful discussions and to the outcome of the iDMEu process THE END 34
R&D CHALLENGES FOR DDNR EXPERIMENTS
▸ In this talk I did not discuss the R&D and technological challenges for DDNR experiments
๏ see https://indico.cern.ch/event/994687/contributions/ 4181753/attachments/2194292/3709516/ baudis_ecfa_feb21.pdf TECHNOLOGICAL CHALLENGES TOWARDS THE NEUTRINO FOG & BEYOND
▸ Upscaling from 10s of kg to tonne scale (crystals) and from tonne to 10s of tonne scale (noble liquids)
▸ Crystal purifcation and growth; operate large crystal arrays; develop new ionisation and phonon sensors
▸ Liquid target purifcation, depletion, cryogenic distillation, storage
▸ Calibration techniques
๏ Input from other communities: material science, chemistry and radiochemistry, engineering, etc BACKGROUND CHALLENGES TOWARDS THE NEUTRINO FOG & BEYOND
▸ Reduce & model cosmogenic background
▸ Reduce and predict in situ activation/production of cosmogenic isotopes underground
▸ Construct Rn-free cleanrooms, workout dedicated cleaning recipes for materials
▸ Continuous cryogenic distillation & crystal growth underground
▸ Understand neutrino backgrounds and uncertainties
๏ Input from other communities: HE particle physics, nuclear physics, chemistry, engineering