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REVIEW 3 major objections 5 minor 297 references

Optimisation of amplification and gas mixture for directional Dark Matter searches with the CYGNO/INITIUM project

T0 review · 3 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

Pith's one-line read This thesis reports that adding a fifth electrode below the last GEM roughly doubles light yield, and that 1.6% SF6 in He:CF4 switches drift to negative ions with diffusion as low as 45 µm/√cm.

desk verdict Solid engineering-physics thesis with two genuinely new results—the extra-electrode light-yield doubling and atmospheric-pressure NID with SF6 optical readout—whose main caveat is that the 45 µm/√cm diffusion value needs a cleaner demonstration that the drifting species is purely ionic. read the letter →

arxiv 2507.02474 v1 pith:A6Y4EZ45 submitted 2025-07-03 physics.ins-det astro-ph.IM

classification physics.ins-detastro-ph.IM
keywords darkmatterdirectdetectionWIMPdirectionalnegativeiondriftSF6gaselectronmultiplieropticalTPCCYGNO
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This thesis is an experimental and statistical study of ways to make the CYGNO optical gas TPC a better directional dark-matter detector. The central hardware claims are that adding a fifth electrode below the last GEM roughly doubles the light yield while shaving tens of micrometres off the amplification-stage diffusion, and that adding 1.6% SF6 to the He:CF4 mixture puts the detector into negative-ion-drift operation with gas gains near $10^4$ and a diffusion coefficient as low as $45\,\mu\mathrm{m}/\sqrt{\mathrm{cm}}$. A third claim is that a future CYGNO-scale detector's directional information improves WIMP exclusion limits and can distinguish two dark-matter models with orders of magnitude fewer events than an energy-only detector. A sympathetic reader would care because directional information is one of the few handles that could turn a dark-matter search into a positive, background-proof identification.

What carries the argument

The load-bearing objects are the segmented amplification and readout chain: a triple stack of 50 µm gas electron multipliers (GEMs) followed by an extra electrode, read out optically by sCMOS cameras for the 2D projection and PMTs for the drift-coordinate timing. The second mechanism is negative ion drift (NID), in which an electronegative additive (SF6) captures primary electrons within micrometers; the resulting heavy negative ions stay thermal with the gas, cutting transverse diffusion while still producing photons during avalanche amplification. The statistical work uses the directional recoil angular distribution, which is peaked toward the Cygnus constellation and cannot be mimicked by backgrounds, inside likelihood-based limits and model-discrimination tests.

What would settle it

Measure the drift time of ionization from a pulsed source across a known drift gap in He:CF4 with 1.6% SF6 and compare the extracted mobility with published mobilities of SF5- and SF6- ions; if the mobility matches electron drift in the same mixture, the negative-ion attribution and the $45\,\mu\mathrm{m}/\sqrt{\mathrm{cm}}$ interpretation fail. A second check is to measure longitudinal diffusion versus drift distance: ion drift should show thermal-level scaling, while electron drift should not.

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Extended reading notes

Core claim

Working with small CYGNO prototypes, the thesis sets out to raise the photon budget and preserve track quality of the optical TPC. It reports that inserting an additional electrode below the last GEM creates strong fields below the holes that boost light production by a factor close to 2 and reduce the intrinsic diffusion of the amplification structure by tens of micrometres, without degrading energy or spatial resolution. It further reports that adding 1.6% SF6 to He:CF4 makes primary electrons attach within a few micrometres, so that negative ions rather than electrons carry the drift signal; this negative-ion-drift operation is demonstrated at atmospheric pressure with gas gains of order $10^4$ and a measured diffusion coefficient as low as $45\,\mu\mathrm{m}/\sqrt{\mathrm{cm}}$. The final part of the thesis uses Bayesian and frequentist likelihoods with the expected CYGNO-30 response to show that directional readout strengthens exclusion limits in the WIMP mass–cross-section plane and that a directional detector can separate a standard halo WIMP signal from a supernova-produced dark-matter signal with far fewer events than a non-directional one.

Load-bearing premise

The load-bearing premise for the hardware claims is that the measured low diffusion in the SF6 mixture really comes from negative-ion drift rather than from electrons that somehow avoid attachment; the statistical projections also presuppose that the angular resolution and head-tail recognition used in the simulation will be achieved by the full-scale CYGNO-30 detector.

Editorial extensions

If this is right

  • The extra-electrode configuration can be adopted in the next CYGNO stages to roughly double the collected light per event, effectively lowering the energy threshold at fixed GEM gain.
  • NID operation with 1.6% SF6 keeps gas gains near $10^4$ while suppressing diffusion to $45\,\mu\mathrm{m}/\sqrt{\mathrm{cm}}$, which should sharpen track reconstruction and head-tail sense identification at low recoil energies.
  • Directional information improves the exclusion limit that CYGNO-30 can set in the WIMP mass–cross-section plane relative to an energy-only analysis.
  • A directional detector can distinguish a standard-halo WIMP signal from a supernova-boosted dark-matter signal with orders of magnitude fewer events than a non-directional detector.
  • The measured amplification-stage diffusion reduction of tens of micrometers directly improves the resolution with which short, low-energy recoil tracks can be imaged.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If NID works at atmospheric pressure with optical readout, the same 1.6% SF6 mixture could be combined with minority-carrier timing to add absolute position along the drift axis, a capability the thesis does not itself demonstrate but that the NID literature suggests.
  • The amplification optimisation is not specific to dark matter; the same recipe could benefit any optical TPC that uses CF4 scintillation and needs more photons per event, such as low-energy electron-scattering or neutrino detectors.
  • The model-discrimination result implies that directional detectors may be able to assign observed recoil events to specific dark-matter production mechanisms, not just to distinguish signal from background.
  • A direct testable extension would be to repeat the NID diffusion measurement with SF6 fractions between 0.5% and 3% to map how diffusion and gain trade off, which the thesis only samples at 1.6%.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. This manuscript is the PhD thesis of G. Dho, posted on arXiv in July 2025, reporting detector R&D for the CYGNO/INITIUM directional dark-matter TPC. Three claims are central. First, in the amplification-stage optimisation study of Chapter 5, the addition of an extra electrode below the last GEM of the triple-GEM stack is reported to increase the light yield by a factor close to 2 in He:CF4 and to reduce the intrinsic diffusion of the amplification structure by tens of micrometres. Second, in Chapter 6, adding 1.6% SF6 to the He:CF4 mixture is reported to produce negative-ion-drift (NID) operation at atmospheric pressure, with gas gains of order 10^4 and a measured diffusion coefficient as low as 45 µm/√cm. Third, in Chapter 7, statistical studies project that the future directional CYGNO-30 detector can improve WIMP cross-section limits relative to non-directional analyses and can discriminate two dark-matter models with orders of magnitude fewer events. Chapters 1-3 provide a standard review of dark-matter evidence, direct-detection phenomenology, and the CYGNO apparatus.

Significance. If the claims hold, this is a solid and useful R&D contribution to gaseous directional dark-matter detection. The two hardware-level results, an electroluminescence-type enhancement of the light yield via an extra electrode below the last GEM, and the demonstration of NID operation at atmospheric pressure with an optical sCMOS/PMT readout, are directly relevant to the CYGNO/INITIUM programme and to the wider CYGNUS effort, since NID is conventionally associated with low-pressure charge readout rather than optical imaging at 1 bar. The statistical part of the thesis is transparent and complete: the directional likelihood used for the exclusion limits and the frequentist model-discrimination setup (WIMP versus supernova-emitted dark matter) are derived in detail, with the velocity-integral calculation given in full in Appendix A; the measured quantities in Chapters 5-6 (gain, light yield, diffusion) are direct observations rather than outputs fitted to the quantities they are claimed to predict, which keeps the amplification study credible.

major comments (3)
  1. [§6.3.1, §6.4] The headline claim that 1.6% SF6 produces NID operation with a diffusion coefficient as low as 45 µm/√cm is load-bearing and depends entirely on identifying the drifting species as negative ions rather than as a mixture of ions and surviving electrons. In the reproduced text, §6.3.1 describes drift-velocity and mobility measurements, but no quantitative SF6 electron-attachment fraction, no search for a prompt electron component in the PMT waveform, and no demonstration that the fitted mobility is field-independent (as expected for a single ion species) are shown. If attachment is incomplete, the sCMOS image integrates the prompt electron signal (arriving on the microsecond scale for a 50 cm drift) together with the delayed ion signal (millisecond scale), and the fitted diffusion coefficient becomes a convolution parameter rather than a pure ion-drift value; even a few percent of surviving electrons could bias the quoted number. Please either present the attachment-fraction measurement and a two-species waveform decomposition, or explicitly demonstrate single-species behaviour (for example, field-independent mobility and an arrival-time versus drift-distance relation with no prompt component), and report the resulting systematic uncertainty on the 45 µm/√cm value; if such tests exist elsewhere in the full thesis, they should be brought into §6.3-6.4 and reported together with the result, because as presented the claim is not fully supported.
  2. [§7.1.2, §7.1.7, §7.2.6] The projected CYGNO-30 limits and the model-discrimination conclusions rest on detector parameters (angular resolution, head-tail recognition efficiency, energy threshold, exposure, and the assumed gain and light yield) that the manuscript states as expectations rather than as measured full-scale performances. The text is honest about this, but the quantitative conclusions of the chapter, namely improved exclusion limits and 'orders of magnitude less events' for model discrimination, are not accompanied by a variation or robustness study over these parameters. I request a sensitivity scan (for example, angular resolution from 15° to 60°, head-tail efficiency from 50% to 100%, and threshold from 1 to 10 keV) to show where the directional advantage degrades or disappears; without it, the projected factors are conditional on unvalidated assumptions and their uncertainty cannot be assessed by the reader.
  3. [§5.3.2, §5.3.4] The abstract's 'factor close to 2' light-yield improvement and 'tens of micrometres' diffusion reduction are the summary claims of Chapter 5, but the reference configuration is not fully pinned down in the reproduced text: the light yield should be quoted per unit charge gain (or at matched total gain and electric fields), the reported diffusion reduction should be identified as transverse and/or longitudinal and connected to the analyses of §4.2-4.3 (55Fe spot shape versus alpha-track transverse profile), and the systematic uncertainties on both numbers should be propagated and quoted. The reviewer's assessment notes that the excerpt does not include the full uncertainty analysis; if it is present in the thesis, the posted version should display it in the results sections so that the factor-of-two headline is reproducible and comparable with the standard CYGNO configuration.
minor comments (5)
  1. [§2.3.2.3] The CYGNO entry of Table 2.2 and the surrounding text give the gas mixture as 'He:CF4 (64/40)', which conflicts with the 60/40 ratio used everywhere else (for example, §3.1.1); please correct this inconsistency.
  2. [§2.1.5.3, §2.3] Equations (2.28) and (2.30) are identical re-statements of the angular-rate dependence; use a cross-reference to the first equation rather than introducing a duplicated numbered formula.
  3. [abstract, §6.5] The phrase 'among the smallest ever measured in a gas detector' should be supported by a short comparison of diffusion coefficients from other NID detectors (for example, DRIFT with CS2-based mixtures and NEWAGE with SF6) or softened, since the reproduced text does not include the comparative values needed to substantiate the claim.
  4. [throughout] Several typos and duplicated words remain, including 'the the', 'Earth's rotation around its own axis', 'T able 1.1', and informal thesis-style passages in the acknowledgements; a careful proofread of the posted version is needed.
  5. [Introduction, §3] A brief explicit statement of which measurements and analyses are the candidate's own work and which are collaboration-level results (for example, LIME data, Garfield simulations, and previously published CYGNO results) would help the reader attribute the claims; this is customary for a thesis and is not clearly visible in the reproduced portion.

Circularity Check

0 steps flagged · score 0.0 of 10

No circular derivation: the thesis's new gain/light-yield/diffusion claims are direct prototype measurements, and its statistical projections use explicitly stated assumed detector parameters rather than fitted inputs.

full rationale

I walked the claimed derivation chain for the main results. The extra-electrode light-yield enhancement (factor close to 2) and the SF6 negative-ion-drift diffusion reduction (45 µm/√cm) are presented as measured quantities obtained with CYGNO prototypes in Chapters 5 and 6, not as quantities derived from a model that already contains them. The drift-velocity/mobility analysis in §6.3.1 is an internal cross-check of the NID identification; even if the attachment fraction is not quantified in the reproduced text, that would be an experimental systematic or correctness concern, not a circular step. Chapter 7 explicitly employs 'future expected performances of the CYGNO experiment' (angular resolution, energy ROI, detector response) as inputs to the Bayesian/frequentist projections; these are stated assumptions, not parameters fitted from data and then relabelled as predictions. The thesis does cite prior CYGNO work, e.g. 'A comprehensive overview of the CYGNO project can be found in [181]' and the 60/40 gas-mixture selection '[193,194]', but those self-citations support the detector concept and gas choice, not the new measurements of light yield, gain, amplification diffusion, or SF6/NID performance; the new results are standalone measurements. I found no equation in which an output equals an input by construction, no renamed fit, and no uniqueness argument whose force depends solely on an author-overlapping citation. The paper is therefore self-contained with respect to its new experimental claims, so the circularity score is 0.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The claimed improvements are supported by direct measurements and simulations; the main free parameters are the assumed performance values used in the future-detector projections, which are not fitted but chosen by hand. No new physical particles or forces are introduced.

free parameters (6)
  • SF6 concentration = 1.6%
    The NID performance (gain, diffusion) depends on this hand-chosen concentration; it is not derived from first principles.
  • Extra electrode voltage = not specified in abstract
    The reported light-yield factor of two corresponds to a tuned operating point; the optimal voltage is an experimental choice.
  • Angular resolution (projection) = assumed in Section 7.2
    The model-discrimination result depends on the assumed angular resolution, which is taken from prototype expectations and not measured at full scale.
  • Head-tail recognition efficiency = assumed in Section 7.2
    HT efficiency strongly affects the directional advantage; the thesis assumes values that are not demonstrated for the full detector.
  • Energy threshold (CYGNO-30) = 1 keVee (claimed)
    Used for the projected exclusion limits; threshold is a key parameter for low-mass sensitivity and is assumed from small prototypes.
  • Exposure (CYGNO-30) = 30 m^3 active volume
    The projected limits are scaled to a conceptual 30 m^3 detector; the reach scales with exposure.
assumptions (5)
  • domain assumption Standard Halo Model: isotropic Maxwell-Boltzmann WIMP velocity distribution with escape-velocity cutoff
    Used in Chapter 7 to compute expected angular and energy distributions; if the real halo is anisotropic or contains streams, the projected directional advantage changes.
  • domain assumption WIMP-nucleus elastic scattering with SI (A^2 coherent) and SD (fluorine) couplings
    Standard direct-detection framework inherited from literature; the limits are set in this parameter space.
  • ad hoc to paper Detector response assumed for CYGNO-30 (gain, angular resolution, threshold) is achievable
    Used in Sections 7.1 and 7.2; the projections are not a measurement of the full-scale detector.
  • domain assumption Electron attachment to SF6 leads to negative ion drift at thermal velocity, producing the low diffusion
    Underpins the interpretation of the measured diffusion in Chapter 6; relies on SF6 electron attachment cross-sections and mobility modeling.
  • domain assumption Garfield and Maxwell simulations accurately model gas avalanche behavior and electric field maps
    Used in Sections 5.4 and Chapter 6 to interpret the experimental results; simulation inaccuracies would affect the conclusions.

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Cite this review

Pith. "Pith review of Optimisation of amplification and gas mixture for directional Dark Matter searches with the CYGNO/INITIUM project." pith.science (2026). https://pith.science/paper/A6Y4EZ45

@misc{pith2026250702474,
  author       = {Pith},
  title        = {Pith review of: Optimisation of amplification and gas mixture for directional Dark Matter searches with the CYGNO/INITIUM project},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/A6Y4EZ45}},
  note         = {Machine review of arXiv:2507.02474}
}
read the original abstract

Astrophysical and cosmological observations suggest the existence of beyond standard model ingredient known as dark matter (DM). One of the most supported class of theories suggests that DM is composed of weakly interactive massive particles (WIMPs), possibly detectable via weak interaction with standard matter resulting in the recoil of the latter. The motion of the Sun and Earth with respect to the Galactic Centre is expected to induce a strong directional dependence in the recoil spectrum. Direct detection experiments capable of measuring the angular features of the recoils gain access to a wide range of advantages such as the possibility to positively claim a discovery of DM. The CYGNO project sets into this context, with the aim of deploying a large directional detector for rare event searches as DM. It exploits a gaseous time projection chamber filled with a He:CF4 gas mixture with a segmented amplification stage and granular optical readout. In this thesis, it is presented the work carried out with small CYGNO prototypes to maximise the light yield without degrading spatial and energy resolution, the addition of highly electronegative gases to induce a reduction of the electron cloud diffusion while drifting towards the amplification stage, very relevant to precisely measure the topological information of the recoil tracks. Moreover, the potential performances of directional detectors in the context of a direct DM search are analysed with the use of rigorous statistical tools both in the improvement in setting limits in the WIMP to nucleon sensitivity and in the capability of discerning two different DM models exploiting a directional detector.

Figures

Figures reproduced from arXiv: 2507.02474 by the authors.

Figure 1.1
Figure 1.1. Example of the rotation curve measurement of the galaxy NGC6503, taken from [5]. The solid line represents the combined fit of the data, while the dashed refers to the gas component, the dotted to the visible one, and the dash-dotted to the DM. [4, 5]. In these galaxies, most of the stars are located in the central part, called bulge, around which largely flat spiral arms composed of stars and gas clouds are moving … view at source ↗
Figure 1.2
Figure 1.2. On the left, a scheme of the working principle of the gravitational lensing (© Horst Frank/Designergold). On the right, an example of a horseshoe Einstein ring due to gravitational lensing taken from a Hubble image [10] [PITH_FULL_IMAGE:figures/full_fig_p019_1_2.png] view at source ↗
Figure 1.3
Figure 1.3. Observation of the bullet cluster performed with the Chandra X-ray tele￾scope [12]. Superimposed in green are the contour lines representing the gravitational potential measured with gravitational lensing. called lens. The angle θ of deflection from the straight path of a light ray passing at a distance r from a lens of mass M is expressed in the simple Schawrzschild approximation by [11]: θ = r 4GM rc2 , (1.8) with… view at source ↗
Figures from the paper (89 more)
Figure 1.4
Figure 1.4. Figure 1.4: CMB anisotropies measured by the PLANCK satellite. Figure by ESA https://www.esa.int/ESA_Multimedia/Images/2013/03/Planck_CMB. from combining and forming the first atoms. This is known as the recombination period. As a consequence, the photons emitted in that era wer…
Figure 1.5
Figure 1.5. Figure 1.5: Temperature anisotropies spectrum in spherical harmonics presented by PLANCK [1]. The blue line is the ΛCDM model fit of the experimental data. Component Density parameter Planck results with 68% CL Radiation Ωr ∼ 9 × 10−5 Baryonic matter Ωb 0.0489 ± 0.0003 Non-baryo…
Figure 1.6
Figure 1.6. Figure 1.6: Example of the N-body simulation result for the Illustris [19]. Different redshift are displayed: top left z=7, top right z=3, bottom left z= 1, bottom right z=0. presence. Since today’s highly inhomogeneous Universe evolved from a very uniform and smooth state at th…
Figure 1.7
Figure 1.7. Figure 1.7: Comoving number density Y as a function of the temperature along the evolution of the Universe for a WIMP mass of 100 GeV/c2 . The solid black line is the solution to the Boltzmann equation that result in the measured DM density parameter Ωnb. The coloured bands show…
Figure 2.1
Figure 2.1. Figure 2.1: Schematics of the scatter between a DM particle χ with momentum p0 and a nucleus A at rest. The nucleus scatters with momentum q at an angle θ. momentum p0 and velocity v which collides with a nucleus A at rest. The latter recoils with momentum q at an angle θ as a r…
Figure 2.2
Figure 2.2. Figure 2.2: The energetic recoil spectra of a Ge target for different WIMP masses, taken from [78]. With lower WIMP mass the spectrum is sharply cut at high energies due to the escape velocity effect on the recoil maximum energy. with α ′ the normalisation factor of the velocity…
Figure 2.3
Figure 2.3. Figure 2.3: Examples of angular distribution of the recoils induced by WIMP inter￾action calculated following the SHM assumptions (for more details see Section 7.2). On the left, the distribution is evaluated using a WIMP mass of 10 GeV/c2 on fluorine target which exhibits the t…
Figure 2.4
Figure 2.4. Figure 2.4: On the left, the γ spectrum above ground and in two underground sites as a function of energy. On the right, the LNGS underground environmental neutron flux [101]. Alphas, positrons and electrons can be more easily stopped, as their energy loss is continuous, and gen…
Figure 2.5
Figure 2.5. Figure 2.5: Neutrino energy spectrum at Earth, integrated over directions and summed over flavours for energies above 100 keV. Figure taken from [107]. block due to the vicinity to the sensitive volume, the best approach is to suppress it as much as possible enhancing the radiop…
Figure 2.6
Figure 2.6. Figure 2.6: The neutrino fog of xenon shown along with some experimental limits on the SI WIMP to nucleon cross section. The colour intensity represents the n index of logarithmic proportionality between the limits on the cross section and the number of CEνNS events detected. Fi…
Figure 2.7
Figure 2.7. Figure 2.7: Schematics of the working principles of the most common detectors for direct searches: (a) scintillating crystal; (b) bolometer; (c) single-phase and (d) dual-phase liquid noble gas detectors; (e) bubble chamber. Figure taken from [36]. In some other cases, the respo…
Figure 2.8
Figure 2.8. Figure 2.8: Current status of the SI limits on the cross section WIMP mass parameter space based on SHM assumption and nuclear recoils searches. Figure taken from [36]. recoils and none ever claimed any discovery. As a consequence, the 90% confi￾dence level exclusion limits are …
Figure 2.9
Figure 2.9. Figure 2.9: On the left the current status of the SD limits on the proton cross sec￾tion WIMP mass parameter space based on nuclear recoils searches. Figure taken from [124]. The most relevant limits are from PICO-60 (blue), PICO-2L (purple), PICASSO (green), SIMPLE (orange), Pa…
Figure 2.10
Figure 2.10. Figure 2.10: Examples of angular distribution of the recoils induced by WIMP inter￾action calculated following the SHM assumptions (for more details see Section 7.2). On the left, the distribution is evaluated assuming a 100% HT recognition, while on the right only 50%, which co…
Figure 2.11
Figure 2.11. Figure 2.11: The angular distribution of the nuclear recoils induced by WIMP and Solar neutrinos in Galactic coordinates. The red line represents the ecliptic path demonstrating a very small overlapping of the two distri￾butions in any moment of the year. Figure from [137]. 2.3.…
Figure 2.12
Figure 2.12. Figure 2.12: On the left, the discovery limits versus DM mass for a fixed detector exposure. On the right, the SI discovery limit as a function of the total detector exposure. Different curves represent, in both panels, the various characteristics these detectors can measure, as…
Figure 3.1
Figure 3.1. Figure 3.1: Sketch of a TPC with some of its feature. The intrinsic 3D nature of the detector, sensitivity to HT and particle identification through the track topology are among the key elements of a TPC based detector. Figure adapted from a drawing. Credit to Oliver Schäfer (DE…
Figure 3.2
Figure 3.2. Figure 3.2: Transverse and longitudinal diffusion coefficients for He:CF4 60/40 (left) and electron drift velocity as a function of the drift field (right). Results obtained by Garfield simulations. Figure taken from [187, 188]. emission spectrum actually comprises two continua,…
Figure 3.3
Figure 3.3. Figure 3.3: Average simulated 3D distance between the production and absorption point for electron and He-nucleus recoils as a function of their kinetic energy in a He:CF4 (60/40) gas mixture. at WIMP masses below 10 GeV/c2 . A systematic optimisation study was performed to defi…
Figure 3.4
Figure 3.4. Figure 3.4: Electron microscope picture of a section of typical GEM electrode, 50 µm thick. The holes pitch and diameter are 140 and 70 µm, respectively. Figure taken from [166]. the contrary, electrons produce longer tracks which translates into less intense spots below 10 keV,…
Figure 3.5
Figure 3.5. Figure 3.5: Sketch of a linear PMT with each component highlighted. On one side there is an input window which covers a photocathode, the sensitive ma￾terial responsible to convert photons into electrons. Inside the tube there are a focusing electrodes, and a sequence of electro…
Figure 3.6
Figure 3.6. Figure 3.6: Examples of PMT waveforms for a track parallel to the GEM plane (left) and tilted with respect to the same plane (right). The difference in time of arrival of the primary charge in the tilted track is mirrored in the time evolution of the waveform. PMTs do not exceed…
Figure 3.7
Figure 3.7. Figure 3.7: Some characteristics of Hamamatsu sCMOS sensors. On the left panel, the readout performances as a function of the photons converted in the sensor with different RMS noise levels in units of electrons for different camera models of different generation (taken from Ham…
Figure 3.8
Figure 3.8. Figure 3.8: Two examples of sCMOS images taken with two CYGNO prototypes, MANGO (left) and LIME (right), of the natural radioactivity (details on the prototypes in Section 3.2). number of photons, permitting direct counting. With the bulk of the photon sensitive region made of s…
Figure 3.9
Figure 3.9. Figure 3.9: Schematic of a lens in the Gaussian approximation taken from [210]. The yellow band refers to the amount of solid angle covered that emitted from the object plane (OP) is focused on the sensor plane (SP). approximation projected on the plane generated by the optical …
Figure 3.10
Figure 3.10. Figure 3.10: Schematic of the roadmap of the CYGNO experiment. Prototype Readout area (cm2) Drift length (cm) Readout Purpose ORANGE 10 × 10 1 1 sCMOS + 1 PMT Proof of technique LEMOn 20 × 24 20 1 sCMOS + 1 PMT Stability and background studies MANGO 10 × 10 1-15 1 sCMOS + 1 PMT …
Figure 3.11
Figure 3.11. Figure 3.11: A simple representation of the MANGO setup with exemplified a triple GEM amplification. Chapter 5 and 6. A sketch of the MANGO prototype and the internal TPC structure is shown in [PITH_FULL_IMAGE:figures/full_fig_p088_3_11.png]
Figure 3.12
Figure 3.12. Figure 3.12: The LEMOn prototype [171]. The elliptical sensitive volume (A), the fast photomultiplier (B), the optical bellow (C) and the sCMOS-based camera (D) are indicated. 3.4 The LEMOn detector A sketch of the Long Elliptical MOdule (LEMOn) detector is shown in [PITH_FULL_…
Figure 3.13
Figure 3.13. Figure 3.13: Detection efficiency for nuclear recoils (ϵ total s ) as a function of their de￾tected energy for an efficiency on 55Fe electron recoils of 4% (squares) and 1% (circles). a medium scale and to measure the energy resolution, the stability performances, to provide a p…
Figure 3.14
Figure 3.14. Figure 3.14: On the left a sketch of the LIME detector. The structure of the acrylic vessel, the copper rings and the optical readout are shown. On the right, a picture of the field cage after the installation. produces the drift field. The amplification stage is based on a trip…
Figure 3.15
Figure 3.15. Figure 3.15: Preliminary results on the linearity study of the LIME detector per￾formed at the LNF. On the left, an example of the light spectrum of the clusters found during the data taking with the 8 keV emission from a copper target material. The data are modelled as a polyno…
Figure 3.16
Figure 3.16. Figure 3.16: The dependence of the average η as a function of the position of the 55Fe source away from the GEM. Credit for this work to the fellow PhD student Rita Joana Cruz Roque. decreasing AG. The ratio η defined as σ/AG is expected to grow with the drift distance [PITH_FU…
Figure 3.17
Figure 3.17. Figure 3.17: Pictures of the ground floor (left) and the first floor (right) with respec￾tively LIME detector inside its Faraday cage and the control room. and its recovery for the disposal of greenhouse gases. In the following Sections, the slow control and DAQ system LIME is e…
Figure 3.18
Figure 3.18. Figure 3.18: On the left an example of two variables of the slow control which check the quality of the data captured with the sCMOS camera. Occurrences of issues was notice by the slow control during this initial test phase. On the right, an example of an image from the sCMOS c…
Figure 3.19
Figure 3.19. Figure 3.19: Result of the GEANT4 simulation of the internal radioactivity of LIME. On the left the sum of the ER and NR induced by radioactive back￾ground interactions. On the right only the NR are shown. The different detector components causing the recoils are separated by me…
Figure 3.20
Figure 3.20. Figure 3.20: Technical design of CYGNO Phase_1 adapted to the Hall F space granted to the CYGNO collaboration. of the film allows the alpha particles from radon daughter decays to enter the fiducial volume and thereby provide a means to tag and remove these events. To further re…
Figure 3.21
Figure 3.21. Figure 3.21: Technical design of CYGNO Phase_1. The 0.4 m3 volume is split in two chambers which share a common aluminised Mylar® cathode. Four sCMOS cameras and twelve PMTs constitute the optical detectors which image the 50 × 80 cm2 readout area. factor ∼ 20 below the internal…
Figure 3.22
Figure 3.22. Figure 3.22: Preliminary technical design of a possible CYGNO Phase_2 located in the Hall C of the underground laboratories of LNGS. damental to positively confirm the Galactic origin of the allegedly detected DM signal. CYGNO-30 could furthermore provide the first directional m…
Figure 4.1
Figure 4.1. Figure 4.1: Example of a sCMOS picture taken with 0.5 s exposure of the natural radioactivity in MANGO. On the left, the original image with the inten￾sity scale shown in gray scale, while on the right, the same picture with superimposed the contours found by the IDBSCAN algorit…
Figure 4.2
Figure 4.2. Figure 4.2: On the left panel an example of the pixels above the noise threshold of an 55Fe spot. The black dot is the evaluated barycentre and the red circle is the one with the maximum radius of ∼ 80 pixels in dimension. On the right panel, the average integral of the 55Fe tra…
Figure 4.3
Figure 4.3. Figure 4.3: A sCMOS image of natural radioactivity taken with the MANGO de￾tector. Different types of tracks are distinguishable with a wide variety of topology. The output of the GAC and the Chan-Vese algorithms are displayed respectively on the left and the right panels. radiu…
Figure 4.4
Figure 4.4. Figure 4.4: On the left, light integral of the selected 55Fe clusters versus the number of pixels belonging to the track np. A strong linear correlation appears evident. On the right, the sum of hundreds of 55Fe tracks after their barycentre was aligned to the same position. for…
Figure 4.5
Figure 4.5. Figure 4.5: On the left, the light integral distribution of the x projection of the 55Fe centred clusters obtained with the two superclustering algorithms described in Section 4.1.3. On the right, the same projection distribution evaluated by the Chan-Vese algorithm with a doubl…
Figure 4.6
Figure 4.6. Figure 4.6: On the left, an example of a transverse profile of an alpha particle sur￾viving the selection cuts described in the text with a Gaussian fit super￾imposed. On the right, an example of a distribution of the σs obtained from the Gaussian fits as of the one left panel. …
Figure 5.1
Figure 5.1. Figure 5.1: A sketch of the internal structure of the TPC of the CYGNO prototypes employed in this study where the addition of the ITO or mesh below the last amplification GEM plane can be appreciated. dedicated to the description of the measurements carried out with the MANGO d…
Figure 5.2
Figure 5.2. Figure 5.2: Example of 1 s exposure picture taken with the sCMOS camera with superimposed four regions the total light was evaluated from. He:CF4 60/40 gas mixture at 1000 mbar, the average atmospheric pressure at Laboratori Nazionali di Frascati (LNF). A ∼ 115 MBq 55Fe source i…
Figure 5.3
Figure 5.3. Figure 5.3: Comparison of the light output and of the charge measured on the ITO glass in LEMOn as a function of the induction field EIT O in He:CF4 60/40 at 1000 mbar. explicitly demonstrating the different rate of increase of the two quantities. The light enhancement measured …
Figure 5.4
Figure 5.4. Figure 5.4: Currents measured in LEMOn as a function of the induction field EIT O for all the six electrodes of the amplification stage plus the ITO glass, where U and D represent respectively the upper and the bottom electrode of each GEM, and the total charge (in gray) is the …
Figure 5.5
Figure 5.5. Figure 5.5: Example of 55Fe signals: on the left, an image acquired by the sCMOS camera in MANGO with a Tt GEM configuration, He:CF4 60/40 gas mixture and 6 kV/cm induction field, where the 55Fe clusters are indi￾vidually identified by the CYGNO reconstruction algorithm [235,241…
Figure 5.6
Figure 5.6. Figure 5.6: Gain scan summarising plot. The light integrals obtained by the 55Fe analysis are shown as a function of the total sum of the voltage applied across the GEMs. Different colours represent the various amplification and gas mixture combinations. events are studied for e…
Figure 5.7
Figure 5.7. Figure 5.7: Relative increase of light integral for the ttt configuration in MANGO and LEMOn.The two data sets are manifestly highly consistent with each other and with the measurements presented in [211], robustly confirming the results presented in Section 5.1.1. In order to i…
Figure 5.8
Figure 5.8. Figure 5.8: On the left, the reduced light gain as a function of VGEM with a linear fit superimposed. On the right, the reduced light gain is expressed as a function of EMesh with a linear fit superimposed in the region below 10 kV/cm. it, the light yield increase becomes expone…
Figure 5.9
Figure 5.9. Figure 5.9: Relative increase of light output as a function of the induction field for all the GEMs stacking configurations studied with MANGO. Config a σa b σb c [cm/kV] σc [cm/kV] d σd Eb [kV/cm] σEb [kV/cm] ttt 60/40 0.99 0.02 0.04 0.02 0.8 0.1 8.2 0.6 9.8 1.5 TT 60/40 0.99 0…
Figure 5.10
Figure 5.10. Figure 5.10: Energy resolution for the different amplification stages as a function of the sum of the voltages applied to the GEMs with a null induction field. Different colours represent the various amplification and gas mixture combinations. configurations appear to display a …
Figure 5.11
Figure 5.11. Figure 5.11: χ function using the parameters found in the fit of the gain from Table B.1. order 104 -105 , the assumption can be considered valid. The first term of the right-hand side of Equation 5.10 is proportional to the Fano term which depends on the Fano factor of the gas …
Figure 5.12
Figure 5.12. Figure 5.12: Energy resolution for the data sets with applied induction fields EMesh as a function of EMesh. Nevertheless, they are common to all the data taking and are not expected to modify the conclusion of this analysis. The energy resolution as a function of the induction …
Figure 5.13
Figure 5.13. Figure 5.13: Primary sigma (averaged from the x and y projections) which represents the diffusion of the amplification structure as a function of the sum of the voltages across the GEMs. Different colours represent the various amplification and gas mixture combinations. backing …
Figure 5.14
Figure 5.14. Figure 5.14: Amplification stage diffusion as a function of the EMesh induction field [PITH_FULL_IMAGE:figures/full_fig_p142_5_14.png]
Figure 5.15
Figure 5.15. Figure 5.15: Raw images of the 55Fe data taking with the TT amplification struc￾ture and 60/40 of He:CF4 gas mixture. On the left a picture with the EMesh = 0 kV/cm, while on the right the field is 11 kV/cm. sCMOS camera is focused on the last GEM electrode (and could not be foc…
Figure 5.16
Figure 5.16. Figure 5.16: Examples of the 2D electric field maps generated by the Ansys Maxwell program. The vertical axis in the figure corresponds to the drift di￾rection. The colour scale represents the intensity of the field, with red being the highest one. On the left, the detailed stru…
Figure 5.17
Figure 5.17. Figure 5.17: Examples of the 2D electric field line maps generated by the Ansys Maxwell program. The vertical axis in the figure corresponds to the drift direction. The line colour scale represents the intensity of the field, with red being the highest one. On the left, the deta…
Figure 5.18
Figure 5.18. Figure 5.18: On the left, the profile of the electric field along the direction orthogonal to the GEM plane which passes through a t GEM hole. The x-axis coor￾dinate refers to the distance from the centre of the GEM hole, positive for above the GEM hole, negative for below, i.e.…
Figure 5.19
Figure 5.19. Figure 5.19: The simulated electric field in the three regions next to the GEM hole are displayed as a function of the induction field EMesh on the left and as a function of VGEM on the right for a thin GEM geometry. Fit parameter At,E (kV/cm) Bt,E At,V (kV/cm) Bt,V (kV/V cm) E1…
Figure 5.20
Figure 5.20. Figure 5.20: Profile of the electric field along the direction orthogonal to the GEM plane which passes through a T GEM hole. The x-axis coordinate refers to the distance from the centre of the GEM hole, positive for above the GEM hole, negative for below, i.e. towards the induc…
Figure 5.21
Figure 5.21. Figure 5.21: The simulated electric field in the three regions next to the GEM hole are displayed as a function of the induction field EMesh on the left and as a function of VGEM on the right for a thin GEM geometry. Fit parameter AT,E (kV/cm) BT,E AT,V (kV/cm) BT,V (kV/V cm) E1…
Figure 5.22
Figure 5.22. Figure 5.22: Rate coefficient of the different excitations (2-5), attachment (6), ioni￾sation (7-13), dissociation (14-16) for CF4 gas interaction with electrons as a function of the reduced electric field taken from [192]. reduced electric field taken from [192]. In particular,…
Figure 6.1
Figure 6.1. Figure 6.1: Reconstructed 3D alpha particles tracks. The z coordinate was obtained by the measurements of the time delay between minority carriers and SF− 6 species. Figure taken from [179] drift distances with respect to ED without significant degradation of tracking properties…
Figure 6.2
Figure 6.2. Figure 6.2: Cross section of the production of SF− 6 (left) and SF− 5 (right) after attach￾ment as a function of the electron energy in eV. Figures taken from [258] hundreds of V/cm, the energy acquired by the electrons before being absorbed is expected to be below tenths of eV.…
Figure 6.3
Figure 6.3. Figure 6.3: Example of PMT waveforms representing tilted alpha tracks obtain with the ED (left) and NID (right) mixtures. The vertical dashed lines on the left panel represent beginning and end of the PMT signal, as estimanted with the algorithm described in the text. The differ…
Figure 6.4
Figure 6.4. Figure 6.4: On the left, NID drift velocity as a function of the drift field. Both data sets at atmospheric pressure and 650 mbar (see Section 6.4.1) and the results extracted from [248] (JINST 13 04 in the legend) are shown in red, blue and grey respectively. On the right, NID …
Figure 6.5
Figure 6.5. Figure 6.5: Example of a 0.5 s sCMOS image acquired with MANGO exposed to the 241Am source placed at 2.5 cm from the GEMs plane and operated with He:CF4 60/40 (left) and He:CF4:SF6 59/39.4/1.6 (right) at atmospheric LNGS pressure (900 mbar). with pixel charge readout in right pa…
Figure 6.6
Figure 6.6. Figure 6.6: On the left, the distribution the sum of the content of the pixels belonging to each cluster (integral) representing an alpha track which survived the selection cuts described in the text. A Gaussian fit is superimposed. On the right, the average light integral as a …
Figure 6.7
Figure 6.7. Figure 6.7: Pictures of the updated MANGO setup. On the left, a detail of the GEM stack equipped with a 15 cm long field cage and the structural support, while on the right, the same structure inserted in the 150 l stainless steel vacuum vessel. GEM amplification plane, the soli…
Figure 6.8
Figure 6.8. Figure 6.8: Estimation of the diffusion as a function of the drift distance for different applied drift fields. ED is shown on the left and NID on the right with superimposed the fit performed with Equation 6.12. The legend shows in colours the different drift fields applied for…
Figure 6.9
Figure 6.9. Figure 6.9: Fitted σ0 (left) and ξ (right) from Equation 6.12 as a function of the applied drift field for ED (black) and NID (red). In right panel the expected thermal behaviour in black and the Garfield++ simulation of the ED gas mixture in blue are also shown. Drift field [V/…
Figure 6.10
Figure 6.10. Figure 6.10: On the left, measured diffusion in ED as a function of the drift distance with 400 V/cm drift field and different voltages VGEM applied on the GEMs (see legend). On the right, fitted ξ from Equation 6.12 as a function of VGEM for the data in the left panel. knowledg…
Figure 6.11
Figure 6.11. Figure 6.11: Light integral as a function of the applied drift, on the left for ED and on the right for NID gas mixture. The legend displays the drift distance of each measurement for both plots. varied. 6.5 Discussion The results illustrated in this Chapter are the first demons…
Figure 7.1
Figure 7.1. Figure 7.1: Quenching factor as a function of the nuclear recoil energy for the various target elements of the gas mixture simulated with the SRIM software. The fitting functions are the representation of the quenching factor behaviour from the Equation 7.7. 1 keVee 0.5 keVee Et…
Figure 7.2
Figure 7.2. Figure 7.2: Two examples of the angular distribution of recoils due to DM in Galactic coordinates, obtained by Monte Carlo simulations. Left: helium recoils induced by 10 GeV/c2 DM. Right: fluorine recoils induced by 100 GeV/c2 DM. of the gas mixtures [PITH_FULL_IMAGE:figures/f…
Figure 7.3
Figure 7.3. Figure 7.3: The probability of each element of being hit and detected as a function of the DM mass, if the energy threshold for the detection is 0.5 keVee. The lower masses are dominated by the lighter element, while above 6 GeV/c2 fluorine is the most probable. The total number…
Figure 7.4
Figure 7.4. Figure 7.4: The µs,90% corresponding to the 90% percentile of the posterior probabil￾ity of µs for two background configurations for the SI coupling and 1 keVee energy threshold. The green and blue points are obtained employing the likelihood of Equation 7.14 which includes the …
Figure 7.5
Figure 7.5. Figure 7.5: Spin-independent 90% C.I. for WIMP-nucleon cross section for 30 m3 CYGNO detector for 3 years of exposure with different background level assumptions and an operative threshold of 1 keVee (top plot) and 0.5 keVee (bottom plot). The dashed curves correspond to a He:CF…
Figure 7.6
Figure 7.6. Figure 7.6: Spin-dependent 90% C.I. for WIMP–proton cross sections for 30 m3 CYGNO detector for 3 years of exposure with different background level assumptions and an operative threshold of 1 keVee (top plot) and 0.5 keVee (bottom plot). The dashed curves correspond to a He:CF4 …
Figure 7.7
Figure 7.7. Figure 7.7: Sky map for the flux of light DM produced by Galactic SNe. The scale has been normalized by NX, the total number of DM particles produced in a single supernova. It is evident that the increased rate of SNe in the Galactic centre results in a large flux from that regi…
Figure 7.8
Figure 7.8. Figure 7.8: Mock example of the possible density distributions of a discriminating variable y in case of two hypotheses H0 and H1. The distribution in blue is the one that follows the hypothesis H0, while the green one follows H1. The red line represents the y0, value chosen as …
Figure 7.9
Figure 7.9. Figure 7.9: Angular distributions of the fluorine recoils for an example of SNDM model (more details on the calculation of the spectra in Section 7.2.4). The different colour represents diverse energy ranges the distribution is evaluated from. The effect of the energy range on t…
Figure 7.10
Figure 7.10. Figure 7.10: Energy (left) and 1D angular recoil spectra (right) for 10 GeV/c2 (top) and 100 GeV/c2 (bottom) WIMP masses for the six scenarios considered. (See [PITH_FULL_IMAGE:figures/full_fig_p203_7_10.png]
Figure 7.11
Figure 7.11. Figure 7.11: Comparison of the angular distribution of nuclear recoils in Galactic coordinates from WIMP on the left and SN DM interactions on the right for the six scenarios considered (1 to 6 from top to bottom), where the colour scale indicates the recoils density. 7.2.5 Like…
Figure 7.12
Figure 7.12. Figure 7.12: The average number of events necessary for discriminating between a WIMP and SNDM signal in the fiducial experimental setups for the various scenarios in [PITH_FULL_IMAGE:figures/full_fig_p208_7_12.png]

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