Experimental Typst web edition · Veto chapter pilot

2 Micromegas X-ray Detectors for BabyIAXO

Introduction

The BabyIAXO Micromegas detectors measure the soft X-rays emerging from the helioscope optics. For photons in the $1 – 10 keV$ region, the detector must provide an energy measurement and identify a localized conversion in the region illuminated by the optics. At surface level, cosmic rays and radiation from the surroundings and detector materials can also deposit energy in the gas. The distribution and timing of the collected charge, together with the activity recorded by the surrounding veto panels, provide the information needed to distinguish X-ray candidates from these backgrounds.

This chapter follows the signal from the entrance window to the calibrated strip waveforms. It explains how photons interact in the gas, how the primary electrons drift and multiply, and how the microbulk Micromegas readout measures the resulting charge. The IAXO-D0 and IAXO-D1 prototypes then provide the concrete setting for the gas, high-voltage, acquisition, and calibration procedures used in the thesis. Their detector response and experimental performance establish the basis for the reconstruction and simulations in Section 3 and the background studies in Section 5.

2.1 Signal Formation in a Micromegas TPC

A time projection chamber (TPC) measures ionization charge after it drifts through a gas volume toward a segmented readout. In the shallow BabyIAXO TPC, the microbulk Micromegas readout amplifies this charge and collects it on two sets of orthogonal strips. The detector therefore records the deposited charge, its two-dimensional distribution, and the relative timing of the strip pulses. These measurements describe both the energy and the shape of an event: a soft X-ray usually produces a localized ionization cloud, whereas many background interactions produce a longer track, several separated deposits, or activity coincident with the veto.

Figure 2.1 shows the stages that produce the signal. An interaction creates electron-ion pairs in the gas, and the drift field transports the electrons toward the readout while the ions move more slowly toward the cathode. The electron cloud spreads during this transport. The electrons that reach the Micromegas amplification region then generate avalanches, producing a charge large enough for the electronics to measure. The following sections connect each stage to the energy, position, and timing information recorded by the detector.

Figure 2.1: Signal formation in a Micromegas time projection chamber (TPC). The illustrative muon track creates electron-ion pairs in the gas. Electrons drift toward the mesh opposite to the drift field 𝐸 𝑑 , while positive ions move toward the cathode. The enlarged view shows electron multiplication between the mesh and anode, where 𝐸 𝑎 ≫ 𝐸 𝑑 . Geometry and multiplication are schematic. — Figure 2.1: Signal formation in a Micromegas time projection chamber (TPC). The illustrative muon track creates electron-ion pairs in the gas. Electrons drift toward the mesh opposite to the drift field $𝐸_{𝑑}$ , while positive ions move toward the cathode. The enlarged view shows electron multiplication between the mesh and anode, where $𝐸_{𝑎} ≫ 𝐸_{𝑑}$ . Geometry and multiplication are schematic.

2.1.1 Entrance-Window Transmission and Gas Conversion

An X-ray emerging from the optics must cross the entrance window before it can interact in the detector gas. The window separates the helioscope vacuum from the gas and must combine mechanical strength with sufficient transmission at low energy. For the aluminized Mylar window used in this detector family, absorption in the polymer film and its metallic coating reduces the number of photons reaching the sensitive volume. This loss is largest at the low-energy end of the signal region.

Photon attenuation through a uniform material of thickness $𝑥$ follows

𝐼 (𝑥) = 𝐼_{0} 𝑒^{- 𝜇 𝑥} .

(2.1)

Here, $𝐼_{0}$ and $𝐼 (𝑥)$ are the incident and transmitted intensities, and $𝜇$ is the linear attenuation coefficient at the photon energy. The equivalent expression $𝜇 = 𝜌 𝜇_{𝑚}$ relates it to the material density $𝜌$ and mass attenuation coefficient $𝜇_{𝑚}$ . The transmission of successive layers is the product of their individual transmissions. Figure 2.2 applies this relation to the aluminum coating and Mylar film and shows how the polymer determines most of the attenuation in the few-kiloelectronvolt region.

Figure 2.2: Calculated X-ray transmission for an aluminized Mylar window model, using the Henke transmission data [ 67 ]. The blue dash-dotted curve represents a 40 nm aluminum layer, and the magenta dashed curve a 4 μm Mylar film. The green solid curve is their product. Window-support obstruction and gas absorption are evaluated separately. — Figure 2.2: Calculated X-ray transmission for an aluminized Mylar window model, using the Henke transmission data [67]. The blue dash-dotted curve represents a $40 nm$ aluminum layer, and the magenta dashed curve a $4 μm$ Mylar film. The green solid curve is their product. Window-support obstruction and gas absorption are evaluated separately.

Once a photon has crossed the window, it must interact before leaving the gas volume. For a path length $ℓ_{gas}$ in a uniform gas, the probability of interaction is $1 - exp [- 𝜇_{gas} (𝐸) ℓ_{gas}]$ . The probability that an incident photon crosses the window and interacts along that path is therefore

𝑃_{w i n + g a s} (𝐸) = 𝑇_{win} (𝐸) [1 - 𝑒^{- 𝜇_{gas} (𝐸) ℓ_{gas}}],

(2.2)

where $𝑇_{win} (𝐸)$ is the window transmission and $𝜇_{gas} (𝐸)$ is the gas attenuation coefficient. In the signal region, photoelectric absorption dominates these interactions and converts the photon energy into ionization. Increasing gas density or path length raises the conversion probability, while the choice of gas changes its energy dependence. The window support introduces a further geometric loss that depends on the illuminated area.

These probabilities describe photon transport before a signal is reconstructed. Some interactions release fluorescence photons that escape, so an interaction need not deposit the full incident energy. Charge collection, the electronic trigger, and event selection introduce additional losses after the conversion. The full detector efficiency must include these effects and the illuminated geometry; the window and gas probabilities alone do not give the acceptance of the final X-ray selection.

2.1.2 Ionization in Gases

For a soft X-ray that interacts in the gas, photoelectric absorption releases a photoelectron that loses energy through excitation and ionization. The resulting electron-ion pairs form the initial charge cloud. The atomic vacancy subsequently relaxes through Auger emission or fluorescence. If a fluorescence X-ray escapes the sensitive volume, the collected charge corresponds to a smaller deposited energy and an escape feature appears in the calibration spectrum. This feature is particularly visible in argon-based $^{55} Fe$ calibrations.

The attenuation coefficients in Figure 2.3 show why noble gases provide the main conversion medium. Their photoelectric absorption is stronger than that of the molecular gases added in small concentrations as quenchers. The quencher contributes less to X-ray conversion but is needed for stable charge amplification, as discussed below.

Figure 2.3: Photon attenuation in gases as a function of energy. The left panel shows the photoelectric attenuation coefficient of noble gases. The right panel compares total attenuation coefficients for saturated hydrocarbons commonly used as quenchers, with argon included for reference as a blue dash-dotted curve in both panels. Data from Ref. [ 68 ], evaluated at 25 ∘ C and 1 bar . — Figure 2.3: Photon attenuation in gases as a function of energy. The left panel shows the photoelectric attenuation coefficient of noble gases. The right panel compares total attenuation coefficients for saturated hydrocarbons commonly used as quenchers, with argon included for reference as a blue dash-dotted curve in both panels. Data from Ref. [68], evaluated at $25^{\circ} C$ and $1 bar$ .

The strong $𝑍$ dependence of the photoelectric cross section in this energy range favors noble gases with greater absorption. The detected spectrum also depends on fluorescence escape and reabsorption, so gas choice affects both the conversion efficiency and the calibration features. Other electromagnetic processes are included in the background simulation, which transports photons and charged particles over a wider energy range than the soft X-ray signal considered here.

Charged particles produce ionization along their path rather than at a single photon-conversion site. Stopping power, multiple scattering, and secondary radiation determine the spatial distribution of this charge, which is typically broader and more elongated than that of an X-ray with an energy of a few kiloelectronvolts. Neutral particles can instead generate nuclear recoils or secondary photons and charged particles in the gas or surrounding materials. These different interactions motivate the combination of radiation transport and detector-response reconstruction used in the background model.

2.1.3 Nuclear-Recoil Ionization and Quenching

Neutrons can produce nuclear recoils in the detector gas. As a recoil slows, it transfers energy to atomic motion and to electronic excitation and ionization. The charge signal measures the resulting ionization, so the recoil energy and its electron-equivalent energy need not coincide. For an electron calibration with reference mean pair-creation energy $𝑊_{𝑒}$ , we define

𝐸_{ee} = 𝑊_{𝑒} ⟨ 𝑁_{ion} ⟩, 𝑞_{ion} (𝐸_{R}) = \frac{𝐸_{ee}}{𝐸_{R}} .

(2.3)

The ionization yield depends on the ion species, energy and gas [69].

Lindhard theory describes the partition between electronic energy and atomic motion over the slowing recoil [70]. For an elemental self-recoil, the conventional parameterization is

𝑄_{L} = \frac{kg (𝜖)}{1 + kg (𝜖)}, 𝜖 = 11.5 𝐸_{R} 𝑍^{- 7 / 3}, 𝑘 = 0.133 𝑍^{2 / 3} 𝐴^{- 1 / 2},

(2.4)

where $𝜖$ is the dimensionless reduced recoil energy, $𝐸_{R}$ is expressed in $keV$ , and $𝐴$ and $𝑍$ are the mass and atomic numbers. The function $𝑔$ is parameterized as

𝑔 (𝜖) = 3 𝜖^{0.15} + 0.7 𝜖^{0.6} + 𝜖 .

(2.5)

Figure 2.4 illustrates the energy dependence for argon and relates one recoil energy to the predicted primary charge.

Figure 2.4: Calculated Lindhard electronic-energy fraction for argon self-recoils, with 𝐴 = 40 and 𝑍 = 18 . The point marks the 10 keV example shown alongside. The charge estimate assumes 𝑞 ion ≃ 𝑄 L . — Figure 2.4: Calculated Lindhard electronic-energy fraction for argon self-recoils, with $𝐴 = 40$ and $𝑍 = 18$ . The point marks the $10 keV$ example shown alongside. The charge estimate assumes $𝑞_{ion} ≃ 𝑄_{L}$ .

Electronic energy includes excitation as well as ionization. Identifying $𝑄_{L}$ with $𝑞_{ion}$ is therefore an approximation for the gas response [69]. The expression contains no pressure, mixture or drift-field parameter, so the charge yield for Ar/isobutane 99/1 at $1.4 bar$ requires separate validation. The example shows how this approximation reduces the primary charge used to predict the waveform amplitude and reconstructed energy.

For a recoil born and stopped in one gas volume, we evaluate the factor at its initial kinetic energy $𝐸_{0}$ and distribute the visible energy over the stored deposits:

𝐸_{ee, 𝑖} = 𝑄_{L} (𝐸_{0}, 𝐴, 𝑍) 𝐸_{dep, 𝑖}, ⟨ 𝑁_{𝑒} ⟩ = \frac{\sum_{𝑖} 𝐸_{ee, 𝑖}}{𝑊_{𝑒}} .

(2.7)

Complete histories with local energy closure and no resolved secondary tracks are required. Deposit positions and times provide the initial charge distribution for electron transport, amplification and waveform reconstruction. Escaping or branching recoils require a different treatment. The proportional allocation remains an approximation; gas-specific yield, charge fluctuations and spatial ionization structure require independent validation before final neutron-background predictions.

2.1.4 Electron Transport and Amplification

An electron-recoil energy deposit $𝐸$ creates a mean number of electron-ion pairs determined by the mean energy $𝑊$ required per pair:

𝑁_{𝑒} = \frac{𝐸}{𝑊} .

(2.8)

The primary-charge fluctuations are commonly expressed through the Fano factor $𝐹$ [71]:

𝜎_{𝑒}^{2} = 𝐹 𝑁_{𝑒} .

(2.9)

For electron recoils, these fluctuations are smaller than Poissonian and contribute to the intrinsic energy resolution. For nuclear recoils, the electron-equivalent energy defined in Section 2.1.3 determines the corresponding mean primary charge.

The drift field carries the electrons toward the mesh. In the mobility approximation, their mean velocity is ${\vec{𝑣}}_{𝑑} = - 𝜇_{𝑒} \vec{𝐸}$ , with the positive mobility $𝜇_{𝑒}$ depending on field, density, and gas composition. Transport properties are often compared through $𝐸 / 𝑝$ , where $𝑝$ is pressure, or $𝐸 / 𝑁$ , where $𝑁$ is the gas number density; the latter also accounts for temperature-dependent density changes. The gas tables used in the developed response model are described in Section 3.4.1.

Collisions spread the electron cloud during drift. After a distance $𝑑$ , its standard deviation along a direction $\hat{𝑢}$ is

𝜎_{\hat{𝑢}} = 𝐷_{\hat{𝑢}} \sqrt{𝑑} .

(2.10)

Here, $𝐷_{\hat{𝑢}}$ has units of square-root length, following the Garfield++ gas-table convention [72]. For uniform drift, it is related to the diffusion coefficient ${𝒟︀}_{\hat{𝑢}}$ , expressed in length squared per time, by $𝐷_{\hat{𝑢}} = \sqrt{2 {𝒟︀}_{\hat{𝑢}} / | {\vec{𝑣}}_{𝑑} |}$ . The longitudinal and transverse spreads in Figure 2.5 describe the cloud along and perpendicular to the mean drift direction.

Figure 2.5: Diffusion of an electron cloud during drift toward the microbulk Micromegas readout. Successive snapshots show the same primary charge with electron losses neglected. The enlarged 1 𝜎 contour has semi-axes 𝜎 𝐿 parallel to the mean drift direction and 𝜎 𝑇 perpendicular to it. Points outside the contour illustrate the tails of the charge distribution. Geometry and relative widths are schematic. — Figure 2.5: Diffusion of an electron cloud during drift toward the microbulk Micromegas readout. Successive snapshots show the same primary charge with electron losses neglected. The enlarged $1 𝜎$ contour has semi-axes $𝜎_{𝐿}$ parallel to the mean drift direction and $𝜎_{𝑇}$ perpendicular to it. Points outside the contour illustrate the tails of the charge distribution. Geometry and relative widths are schematic.

Transverse diffusion shares charge between neighboring strips, while longitudinal diffusion spreads its arrival times. The measured pulse width also includes electronic shaping and reconstruction, so it cannot be identified directly with the longitudinal cloud width. Recombination and attachment reduce the charge reaching the mesh; gas purity and the removal of oxygen and water therefore affect both amplitude and stability.

In the narrow amplification gap, a stronger field allows the electrons to ionize the gas and generate avalanches. Neglecting electron losses, the mean amplified electron population is

𝑁_{𝑎} = 𝐺 𝑁_{𝑒},

(2.11)

where $𝐺$ is the mean gas gain. For independent avalanches, let $𝑏 = 𝜎_{𝐺}^{2} / 𝐺^{2}$ denote the relative single-electron gain variance. With independent additive electronic noise $𝜎_{el}$ referred to the amplified charge, the relative full width at half maximum (FWHM) of an approximately Gaussian peak is

𝑅 \approx 2.35 \sqrt{\frac{𝐹 + 𝑏}{𝑁_{𝑒}} + {(\frac{𝜎_{el}}{𝐺 𝑁_{𝑒}})}^{2}} .

(2.12)

This expression separates primary-ionization statistics, avalanche fluctuations, and electronic noise [73]. Charge losses and fluctuations shared across an event can broaden the measured peak further; calibration tests the combined detector response.

Avalanche ultraviolet photons can initiate further avalanches through photoionization or electron emission from surfaces. Isobutane suppresses this feedback through absorption and nonradiative molecular relaxation. It also changes drift and diffusion, so its concentration affects both stable amplification and the charge distribution reaching the readout.

2.1.5 Micropattern Gaseous Detectors: Micromegas

Micromegas (MICRO-MEsh GAseous Structure) detectors separate the drift volume from a narrow amplification gap with a thin metallic mesh [74]. The relatively weak drift field carries the primary electrons toward the mesh. With a suitable ratio between drift and amplification fields, the electrons pass through its openings and enter the high-field gap, where they multiply before reaching the anode strips. This separation allows charge transport and amplification to be controlled through different fields while retaining fast signals and fine spatial segmentation.

For axion helioscopes and other rare-event searches, microbulk Micromegas provide a thin readout with a small material budget. Photolithographic processing of copper-clad Kapton forms the mesh, insulating pillars, and readout pattern in a mechanically uniform structure [75]. The use of radiopure copper and Kapton reduces the activity close to the gas, while the orthogonal strips resolve the two-dimensional distribution of the collected charge. These properties combine efficient soft X-ray detection with the spatial information needed to reject many extended background events.

The IAXO-D1 readout has three distinct length scales. Its $6 cm$ width contains 120 strips per coordinate, corresponding to a strip pitch of $500 μm$ . At each X–Y strip crossing, the IAXO-D1 mesh photograph resolves a $3 \times 3$ group of microscopic openings. Microbulk structures in this detector family have holes of order $40 μm$ in diameter on an approximately $100 μm$ triangular pitch, with an amplification gap of approximately $50 μm$ defined by the etched polyimide [56, 76]. The strip pitch sets the readout granularity, whereas the smaller holes and gap determine electron transmission and avalanche formation. Figure 2.6 shows how the mesh and the two strip coordinates fit together.

Figure 2.6: Simplified microbulk Micromegas readout with orthogonal X and Y strip pixels beneath a perforated copper mesh. The design follows the BabyIAXO readout in Figure 2.10 , reduced from 120 + 120 strips to 8 + 8 . X-strip pixels connect in the same printed circuit board (PCB) layer, while Y-strip pixels connect through the bottom layer. In the detector, an approximately 50 μm amplification gap separates the mesh from the readout. The drift volume above the mesh is not shown. — Figure 2.6: Simplified microbulk Micromegas readout with orthogonal X and Y strip pixels beneath a perforated copper mesh. The design follows the BabyIAXO readout in Figure 2.10, reduced from $120 + 120$ strips to $8 + 8$ . X-strip pixels connect in the same printed circuit board (PCB) layer, while Y-strip pixels connect through the bottom layer. In the detector, an approximately $50 μm$ amplification gap separates the mesh from the readout. The drift volume above the mesh is not shown.

The operating fields must transmit electrons through the mesh and provide enough gain to resolve a kiloelectronvolt signal above noise. At a fixed mesh voltage, scanning the drift field with an X-ray source identifies the transmission plateau, where the calibration peak position is approximately constant. Increasing the amplification field within this region then raises the gain until discharge behavior limits operation. The peak position, width, and discharge rate together define a suitable operating range for each gas, pressure, and electronics configuration [77]. These characterization scans establish the operating point; Table 2.2 lists the recorded conditions of the R02729 reference acquisition.

The combination of radiopurity, segmentation, low threshold, and operation in CAST underpins the use of microbulk Micromegas in the IAXO experiment [12, 16, 42]. The next section describes how these principles are implemented in the two prototype generations used in this thesis.

2.2 The BabyIAXO Micromegas Detector Prototypes

The BabyIAXO detector prototypes retain the compact TPC and segmented microbulk readout developed for CAST. The cylindrical gas volume has a diameter of $10 cm$ , a drift length of $3 cm$ , and a volume of approximately $236 {cm}^{3}$ . A square readout of side length $6 cm$ collects the charge on 120 strips in each coordinate, giving 240 channels. The gas depth sets the conversion probability and maximum drift distance, while the strips measure the two projections of the ionization cloud.

Solar X-rays are concentrated near the center of the readout by the telescope, whereas background interactions can occur throughout the chamber. The background analysis therefore uses a fiducial region smaller than the full $6 cm \times 6 cm$ readout. The adopted criterion requires the paired X–Y center of the calibrated maximum-energy reconstructed track to satisfy $𝑟 < 10 mm$ , giving $𝐴_{fid} = 𝜋 {cm}^{2}$ . Earlier studies used a $15 mm$ -radius region, either to integrate readout energy or to select the hit centroid; their results retain that separate definition. The baseline selection and its rate normalization are described in Section 5.1.7.

IAXO-D0 and IAXO-D1 share the TPC dimensions, readout size, number of strips, and nominal lead-shielding thickness. Their differences concern how the chamber, pipe, readout connections, and electronics fit inside the shielding and how the detector can be accessed. Table 2.1 summarizes these differences and identifies the role of each prototype in this thesis.

Feature	IAXO-D0	IAXO-D1
Role	Detector derived from the final CAST design, used in Zaragoza campaigns, veto tests, and comparisons with simulation.	Prototype developed for BabyIAXO chamber integration, detector access, and updated electronics.
Chamber and shielding	Cylindrical chamber, brick-based lead shielding, and protruding copper backplate.	Square-footprint chamber, thicker pipe, movable lead shielding, and inner copper liner.
Readout integration	Rigid readout connection through flat cables to a combined front-end card (FEC)–Feminos unit.	Flexible Micromegas PCB and front-end placement closer to the readout to reduce cable length.
Electronics	AGET front-end chips with Feminos back-end electronics.	STAGE front-end chips with ARC-compatible back-end electronics in the intended architecture; AGET/Feminos used in the SOLEIL measurements.
Thesis use	Early detector-operation and veto-integration studies.	Reference geometry for the argon background model and basis for the separate BabyIAXO projection.

Table 2.1: Comparison of the IAXO-D0 and IAXO-D1 Micromegas prototypes and their roles in this thesis. The intended D1 electronics architecture is distinguished from the AGET/Feminos system used for the published spatial-resolution measurements [78].

The simulation geometries in Figure 2.7 show how these changes affect the material surrounding the gas and the openings through the shield. The D0 backplate extends laterally beyond the lead bricks, while the D1 chamber fits within a movable shield and connects to a thicker copper pipe. These structures must be represented separately when calculating radiation transport to the gas.

(a) IAXO-D0: cylindrical chamber, brick shielding, and laterally protruding copper backplate.

(b) IAXO-D1: square chamber, movable monolithic shielding, thicker pipe, and inner copper liner. — (a) IAXO-D0: cylindrical chamber, brick shielding, and laterally protruding copper backplate.

2.2.1 IAXO-D0

The IAXO-D0 chamber is cylindrical and closes with a large copper backplate that extends laterally from the shielding. Its copper pipe has a thinner central section, and the lead shield is built from bricks. Access to the chamber requires removing part of this shield, making detector interventions dependent on its disassembly. Four AGET chips read the strips through flat cables connected to a combined front-end card (FEC)–Feminos unit; the Feminos card supplies the back-end electronics [79].

The Zaragoza campaign used a Micromegas readout shortly after its decommissioning from CAST to study the detector response and test rejection of cosmic-ray-induced background with the prototype veto. Earlier campaigns used other readouts from the same prototype generation [80]. These campaigns established the detector-operation and veto-integration procedures used in this thesis.

2.2.2 IAXO-D1

The IAXO-D1 design provides access to the detector by moving the lead shield laterally on linear rails. The shield forms a box with a central square shaft around a chamber with a square footprint and a thicker copper pipe. A flexible Micromegas PCB carries the strip connections parallel to the pipe through the shielding aperture. This arrangement allows the readout and its services to fit within the shield while retaining access to the chamber. The identified D1 calibrations supply the measured reference for the quantitative detector-response comparisons in Section 3.

Figure 2.8 compares the chamber used in the simulation with the assembled detector. The copper walls provide the mechanical enclosure, and the inner polytetrafluoroethylene (PTFE) liner helps suppress copper fluorescence reaching the gas [78]. The field-shaping ring lies outside this liner and is intended to reduce distortions of the drift field near the chamber boundaries.

Figure 2.8: IAXO-D1 detector chamber. The left panel shows the simplified simulation geometry, and the right panel shows the assembled chamber. The electric-field shaping ring lies outside the polytetrafluoroethylene (PTFE) liner. Two gas lines, one of which is not shown, run parallel to the pipe. The chamber backplate and body are fastened to the pipe with 12 copper bolts.

The exploded view in Figure 2.9 identifies the layers between the beam pipe and the readout. The thin entrance window seals the gas volume and acts as the cathode, while its supports withstand the pressure difference across the window. The readout and mesh close the opposite end of the drift region, where the arriving electrons are amplified and collected.

Figure 2.9: Exploded view of the IAXO-D1 detector chamber created using the simplified simulation geometry from Figure 2.8 . The copper backplate (a), readout PCB (b), readout/mesh (c), chamber copper walls (d), chamber inner PTFE lining (e), ultrathin aluminized Mylar window (f), conductive copper cathode support (g), and PTFE cathode support (h) are shown. The cathode parts (f, g, h) are glued together into a single assembly. The copper-covered readout PCB (b) supports the microbulk foil and carries its electrical connections. — Figure 2.9: Exploded view of the IAXO-D1 detector chamber created using the simplified simulation geometry from Figure 2.8. The copper backplate (a), readout PCB (b), readout/mesh (c), chamber copper walls (d), chamber inner PTFE lining (e), ultrathin aluminized Mylar window (f), conductive copper cathode support (g), and PTFE cathode support (h) are shown. The cathode parts (f, g, h) are glued together into a single assembly. The copper-covered readout PCB (b) supports the microbulk foil and carries its electrical connections.

The PCB must bring all 240 strip signals outside the active area without interrupting the two-coordinate readout. Figure 2.10 shows the routing reconstructed from the Gerber layers. One strip direction is connected in the top copper layer and the other through the bottom layer, preserving the orthogonal pixel pattern introduced in Figure 2.6.

Figure 2.10: IAXO-D1 Micromegas PCB reconstructed by combining its Gerber layers. Panel (a) shows the complete PCB: top-copper features are yellow, bottom-copper routing is orange, and mounting holes are blue. The connector pads for the 240 strips are grouped on the left, while the square active readout occupies the center-right. Panel (b) shows an enlarged and rotated readout corner. The yellow pixels are arranged in orthogonal strips, with one strip direction connected through the bottom copper layer. The simplified model in Figure 2.6 is based on this design.

Figure 2.11 follows the readout from its flexible extension to its installation and then to the microscopic mesh pattern. The flexible section accommodates the chamber and shielding geometry; the perforated mesh and strip pattern determine how the avalanche charge is collected across neighboring channels.

Figure 2.11: IAXO-D1 microbulk Micromegas readout. Panel (a) shows the readout and its flexible PCB extension before installation, panel (b) shows the square active area installed in the chamber, and panel (c) is an optical-microscope close-up of the perforated copper mesh. The close-up resolves the 3 × 3 hole group associated with each 500 μm -pitch strip crossing. — Figure 2.11: IAXO-D1 microbulk Micromegas readout. Panel (a) shows the readout and its flexible PCB extension before installation, panel (b) shows the square active area installed in the chamber, and panel (c) is an optical-microscope close-up of the perforated copper mesh. The close-up resolves the $3 \times 3$ hole group associated with each $500 μm$ -pitch strip crossing.

The intended D1 electronics place four STAGE chips on FECs close to the readout and an ARC-compatible back-end outside the passive shield (Figure 2.12(a) and Figure 2.12(b)). Keeping the analog connection short reduces its capacitance and exposure to noise pickup. This placement also brings the FEC materials close to the gas, where radioactive contamination can contribute to the background. The March 2025 electronics report lists radiopure PCB substrates but does not classify the populated cards as fully radiopure; the mounted components and connectors must therefore remain in the material-background inventory [81]. The back-end contains more conventional components and is placed outside the shield, with flexible interconnects carrying data and control signals through the penetration. The same report describes produced boards whose FEC–back-end link still required testing, so this layout specifies the intended architecture rather than the electronics used in every D1 acquisition.

(b) Back-end electronics. — (a) Front-end card (FEC).

2.3 Detector Ancillary Systems

Stable gas composition, pressure, and electrode voltages are needed to maintain the detector response throughout a run. Gas lines and electrical cables pass through the shielding and must allow access to the chamber; the acquisition separately synchronizes the Micromegas and veto signals.

2.3.1 Gas System

The prototypes can operate with argon–isobutane or xenon–neon–isobutane mixtures. CAST operated mainly with argon and 2% isobutane at $1.4 bar$ [12]; its final campaigns used equal partial pressures of xenon and neon with $2.3 %$ isobutane [42]. The xenon–neon mixture removes the argon escape structure near the signal region and the intrinsic $^{39} Ar$ contribution. Because xenon is costly, recovering the gas through purification and recirculation becomes an important operating requirement.

In a closed loop, contaminants introduced by the chamber, pipework, pump, buffer volume, valves, and filters can remain in the circulating gas. Leaks and outgassing affect electron transport, while radon emanation can introduce radioactive decays in or near the conversion volume. IAXO-D1 measurements found substantial changes in the low-gain alpha rate between open-loop and recirculating configurations, motivating checks of radon sources and purification methods [82]. Chemical purification and radiological control are therefore both needed when evaluating a recirculation system.

The mixture composition, pressure, temperature, drift field, flow stability, and gas purity determine the transport conditions during each measurement. These conditions must be matched when choosing the gas tables for simulation, since changes in drift velocity, diffusion, or electron attachment alter the recorded charge distribution. Section 3.4.1 describes the calculation of these properties with Garfield++ and Magboltz. Open-loop operation exhausts the used mixture; closed-loop operation recirculates it through purification. Evacuation assists gas changes, and pressure relief protects the entrance window.

2.3.2 High Voltage and Slow Control

Separate high-voltage channels bias the cathode and mesh to establish the drift and amplification fields. Voltage changes affect electron transport, mesh transparency, avalanche gain, and the reconstructed event shape. The veto photomultiplier tubes are biased independently, and their gain affects the threshold and timing of the coincident signals. Controlled voltage ramps, current monitoring, and filtering help maintain stable operation. If the current exceeds the protection threshold, the supply trips and switches off the high voltage to protect the detector during a discharge.

The slow-control system records the voltages together with the gas and environmental conditions so that changes in gain or noise can be compared with the operating history. It also allows remote intervention during long runs. We developed the reusable hvps control library to operate the high-voltage supplies; its implementation is described in Section 3.8.3.

2.3.3 Shielding and Veto Integration

Passive shielding attenuates external radiation before it reaches the gas, while the active veto records coincident activity around the detector. The pipe, gas lines, electrical feedthroughs, and calibration access create openings that must be included when assessing the complete detection line. Micromegas waveforms provide the X-ray candidate and its timing reference; the synchronized veto signals then identify activity associated with that event. Section 4 develops the passive-shielding studies, cosmic-ray-induced background simulations, and scintillator–cadmium veto design using this combined information.

2.4 Data Acquisition System

The data acquisition (DAQ) system records the strip waveforms and the surrounding veto activity associated with a trigger. The front-end card (FEC) amplifies and shapes the strip signals, the front-end module (FEM) controls their digitization and readout, and the DAQ computer stores the events. Their timing must be coordinated so that a TPC candidate can be compared with pulses in the veto panels. The acquisition software developed in this thesis, including the feminos-daq refactor and online viewer, is described in Section 3.8.2.

The prototype acquisition follows the AGET/Feminos approach used for the IAXO pathfinder at CAST. In the pathfinder, four AGET chips read the 240 Micromegas strips, and an otherwise unused channel recorded the external muon-veto signal [77]. The commissioned prototype chain expands this arrangement into separate TPC and veto branches, synchronized through a common Trigger Clock Module. Figure 2.13 shows how this connection preserves the information needed to associate the two detectors event by event.

Figure 2.13: Synchronized Micromegas and veto acquisition in the commissioned IAXO-D0 prototype, following the AGET/Feminos readout approach used at CAST [ 77 ]. Separate TPC and veto branches share a timing reference before their signals are combined into an event. The STAGE/ARC architecture described for IAXO-D1 is a separate electronics development. — Figure 2.13: Synchronized Micromegas and veto acquisition in the commissioned IAXO-D0 prototype, following the AGET/Feminos readout approach used at CAST [77]. Separate TPC and veto branches share a timing reference before their signals are combined into an event. The STAGE/ARC architecture described for IAXO-D1 is a separate electronics development.

Four AGET chips acquire the TPC strips, while Feminos supplies configuration, timing, readout control and Ethernet transfer [79, 83]. The IAXO-D1 calibration measurements used an AGET/Feminos TPC readout. The detector generation and electronics generation must therefore be identified separately when comparing measurements.

2.4.1 Run Conditions and Waveform Observables

The acquisition records identify the detector conditions and electronics settings used for each run. Gas composition and pressure determine electron transport, while the cathode and mesh voltages establish the drift and amplification fields. Electronic gain, shaping and sampling then determine how the collected charge appears in the waveform. Table 2.2 records the R02729 reference acquisition. Figure 2.14 summarizes the settings of the $40$ calibration runs compared in Section 3.6.

Setting	R02729 reference acquisition
Date	May 28, 2025
Nominal gas	Ar–isobutane (99:1)
Recorded pressure	$1.4 bar$
Mesh / cathode voltage magnitudes	$335 V$ / $800 V$
Nominal drift distance	$30 mm$
Calculated drift field	$155 V {cm}^{- 1}$
Sampling period	$40 ns$
DAQ gain / shaping codes	`0x0` / `0xF`
Nominal shaping time	$1014 ns$

Table 2.2: Recorded and nominal conditions of IAXO-D1 reference run R02729. Pressure and voltage magnitudes come from the acquisition header; gas composition and drift distance are nominal. The drift field uses the voltage difference over the drift distance. The sampling period comes from the saved reconstruction settings, and the shaping time follows the nominal configuration for 0xF.

Figure 2.14: Recorded settings of the 40 IAXO-D1 calibration acquisitions used in the completed response comparisons, from May 8 to December 12, 2025. Each run contributes once, irrespective of its event count or duration. Colors and hatching identify the two gain/shaping groups; dashed lines mark R02729. Voltages are acquisition-header magnitudes, and the drift field uses their difference over the nominal 30 mm drift distance. The field histogram uses 5 V cm − 1 -wide bins; the other panels count discrete settings. Gain and shaping labels are recorded configuration codes; the distributions describe this calibration sample. — Figure 2.14: Recorded settings of the $40$ IAXO-D1 calibration acquisitions used in the completed response comparisons, from May 8 to December 12, 2025. Each run contributes once, irrespective of its event count or duration. Colors and hatching identify the two gain/shaping groups; dashed lines mark R02729. Voltages are acquisition-header magnitudes, and the drift field uses their difference over the nominal $30 mm$ drift distance. The field histogram uses $5 V {cm}^{- 1}$ -wide bins; the other panels count discrete settings. Gain and shaping labels are recorded configuration codes; the distributions describe this calibration sample.

The mesh voltage magnitude spans $320 – 335 V$ and the cathode magnitude spans $700 – 850 V$ , giving calculated drift fields of $123.3 – 175 V {cm}^{- 1}$ . The two gain/shaping groups contain $23$ and $17$ runs. All $40$ runs have a recorded pressure of $1.4 bar$ , nominal Ar–isobutane (99:1), and a sampling period of $40 ns$ in the reconstruction settings. These distributions show which conditions changed between calibrations; a stability measurement would also require their time dependence and the measured peak positions.

A pedestal acquisition measures the mean $𝑚_{𝑖}$ and standard deviation $𝜎_{𝑖}$ of the quiet signal in each channel. Feminos subtracts the channel means and restores a common baseline, usually 250 analog-to-digital converter (ADC) counts. A channel can generate a trigger when its amplitude exceeds a threshold relative to this baseline; the prototype procedure described here uses three pedestal standard deviations. The readout can return all channels or only those passing its channel threshold. These choices affect both the measured charge and the number of strips available to reconstruct a low-energy event. Figure 2.15 illustrates the display of signals from active strips.

Figure 2.15: Measured strip waveforms from R02729 event 5484, separated into X and Y projections and labeled by physical strip coordinate. The original pedestal and common-noise corrections are retained; a residual mean estimated over samples 20–199 is removed before restoring a baseline of 250 ADC counts for display. Only strips with peak amplitudes above 500 ADC counts relative to this baseline are shown. The 8.5 – 12.5 μs window is part of a 512-sample record with 40 ns sampling. — Figure 2.15: Measured strip waveforms from R02729 event 5484, separated into X and Y projections and labeled by physical strip coordinate. The original pedestal and common-noise corrections are retained; a residual mean estimated over samples 20–199 is removed before restoring a baseline of 250 ADC counts for display. Only strips with peak amplitudes above 500 ADC counts relative to this baseline are shown. The $8.5 – 12.5 μs$ window is part of a 512-sample record with $40 ns$ sampling.

The signal in each active strip has an amplitude and arrival time, together with a width set by charge transport and the shaping electronics. Figure 2.16 illustrates how these quantities are measured relative to the restored baseline. Pulse height and integral provide charge estimators, while relative pulse times describe the extent of the event along the drift direction. The threshold-selected integral sums the baseline-subtracted signal in samples that pass the threshold. The reconstruction used in this thesis obtains energy from fitted pulse amplitudes, as detailed in Section 3.4.6. The rise and fall times also help identify pileup or signals that differ from the expected shaped response.

Figure 2.16: Waveform observables illustrated with a generated pulse. Panel (a) defines the baseline 𝐵 , peak amplitude 𝐴 , peak time 𝑡 𝑝 , and first threshold crossing 𝑡 th . The hatched area represents the sum of baseline-subtracted samples above the threshold. Panels (b) and (c) show the rise time from 15% to 85% and fall time from 85% to 15% of the peak amplitude relative to the baseline. The horizontal axis counts sample bins; the pulse and threshold values are illustrative. — Figure 2.16: Waveform observables illustrated with a generated pulse. Panel (a) defines the baseline $𝐵$ , peak amplitude $𝐴$ , peak time $𝑡_{𝑝}$ , and first threshold crossing $𝑡_{th}$ . The hatched area represents the sum of baseline-subtracted samples above the threshold. Panels (b) and (c) show the rise time from 15% to 85% and fall time from 85% to 15% of the peak amplitude relative to the baseline. The horizontal axis counts sample bins; the pulse and threshold values are illustrative.

Shaping time controls the pulse width, and the sampling period fixes its time granularity. The trigger delay determines how much baseline precedes the pulse and how much of its tail is retained. A threshold that removes low-amplitude strips can reduce the reconstructed energy and narrow the apparent charge distribution. For this reason, data and simulation must use compatible acquisition settings before their reconstructed observables can be compared.

Figure 2.17 illustrates how spatial extent and relative pulse timing distinguish a compact charge cloud from an extended ionization track. Charge distributed along the drift direction reaches the mesh at different times, even when its transverse projection is small. A track nearly parallel to the drift direction can therefore resemble an X-ray in the strip plane while producing a wider arrival-time distribution. Some background interactions also produce localized deposits, so compactness alone cannot identify the incident particle.

Figure 2.17: Schematic comparison of a compact X-ray-like charge cloud and an extended ionization track. Panels (a) and (b) show one strip projection against charge-arrival time, with marker size indicating relative charge; panels (c) and (d) show four illustrative strip pulses. Both columns use the same dimensionless position, time and amplitude scales, with each pulse normalized to unit peak height. These conceptual patterns illustrate the observables rather than measured or simulated events.

Reconstruction combines the strip amplitudes and times with their positions to form hits and tracks. The resulting energy estimators measure the charge through pulse heights, integrals or reconstructed hits. Widths, hit counts, charge balance and asymmetry describe how that charge is distributed. These quantities connect the detector physics developed earlier to the event selection used in the following chapters.

2.5 Detector Calibration

Calibration relates the recorded charge to deposited energy and checks whether the response remains stable between runs. Changes in gas purity, pressure, voltage or electronics noise can shift a photopeak or alter its width. We therefore compare calibration spectra and detector conditions before transferring an energy scale to a background acquisition. At the CAST pathfinder, regular $^{55} Fe$ measurements supplied the nearby calibration used for each background or tracking period [77]. The same principle applies to the prototype measurements: the calibration must describe the conditions under which the physics data were recorded.

2.5.1 Standard X-ray Calibration

A source placed in front of the entrance window produces X-rays with known energies in the detector gas. The routine source is $^{55} Fe$ , whose dominant manganese $𝐾_{𝛼}$ line at $5.9 keV$ lies within the signal region. Its photoelectric conversions provide localized charge clusters for measuring the energy scale and checking reconstructed shapes. Sources such as $^{109} Cd$ can add higher-energy points when testing the response over a wider interval.

The reconstructed position map first checks that the source illuminates the expected region and that no inactive area or large asymmetry has appeared. The photopeak position then measures the charge scale, while its width describes the combined fluctuations of ionization, collection, amplification and readout. Comparing these quantities between calibrations distinguishes a stable response from a change associated with detector operation. A numerical stability result requires a sequence of measured runs; the single-run spectrum below illustrates the calibration features.

In argon, the $5.9 keV$ photopeak and the escape structure around $2.9 keV$ provide two energy anchors [77]. They can determine both the scale and offset of a linear calibration. For xenon-based operation, the main line determines a one-point scale when a zero offset is assumed. Additional lines or calibrated charge injection are then needed to test that assumption and the linearity of the response. The accepted calibration is applied before event selection; it is not readjusted to increase the fraction of simulated events passing the analysis requirements.

Figure 2.18 shows the measured R02729 calibration used as the reference for the response comparisons in Section 3. The spectrum contains $9956$ valid reconstructed events from a $10000$ -entry sample, before the TPC baseline selection. Its energy estimator combines the fitted amplitudes of the maximum-energy tracks in the two strip views. The main manganese photopeak and argon escape feature illustrate full-energy absorption and fluorescence escape under the conditions in Table 2.2. The main peak is fitted with two Gaussian contributions for manganese $𝐾_{𝛼}$ and $𝐾_{𝛽}$ , with fixed relative energies and integrated intensities and widths proportional to the square root of energy. The fitted $𝐾_{𝛼}$ FWHM divided by its centroid is $26.3 %$ for this sample and fit interval; the fit does not change the accepted energy scale. The response comparison in Section 3.6.3 uses a separate Gaussian core-width definition.

Figure 2.18: Measured 55 Fe calibration spectrum for IAXO-D1 run R02729, using the same valid reconstructed sample and energy estimator as Section 3.6 . The density is normalized to all 9956 valid events, including the 193 above the displayed 0 – 12 keV interval; 9763 events lie within it. Bins are 0.25 keV wide, and bars show 68.27% Wilson intervals for the bin fractions divided by the bin width. The solid blue curve is the manganese-doublet fit over 4.75 – 6.75 keV , using 0.071 keV -wide fit bins; dotted blue segments extrapolate the model outside this interval. The orange and purple curves show the fitted 𝐾 𝛼 and 𝐾 𝛽 contributions. The marker near 2.9 keV indicates the nominal argon escape energy; this feature and the spectral tails are not fitted. The spectrum precedes the TPC baseline selection. — Figure 2.18: Measured $^{55} Fe$ calibration spectrum for IAXO-D1 run R02729, using the same valid reconstructed sample and energy estimator as Section 3.6. The density is normalized to all $9956$ valid events, including the 193 above the displayed $0 – 12 keV$ interval; $9763$ events lie within it. Bins are $0.25 keV$ wide, and bars show 68.27% Wilson intervals for the bin fractions divided by the bin width. The solid blue curve is the manganese-doublet fit over $4.75 – 6.75 keV$ , using $0.071 keV$ -wide fit bins; dotted blue segments extrapolate the model outside this interval. The orange and purple curves show the fitted $𝐾_{𝛼}$ and $𝐾_{𝛽}$ contributions. The marker near $2.9 keV$ indicates the nominal argon escape energy; this feature and the spectral tails are not fitted. The spectrum precedes the TPC baseline selection.

This measured spectrum establishes the experimental reference; the comparison with reconstructed simulations, event shapes, and selection acceptance follows in Section 3.6.

2.5.2 Spatial-Resolution Measurements at SOLEIL

The published SOLEIL measurements provide a direct test of the D1 position reconstruction [78]. The detector operated with argon and $5 %$ isobutane at atmospheric pressure, an open gas flow of $5 L h^{- 1}$ , and a mesh-voltage magnitude of $360 V$ . The measurements used AGET/Feminos electronics, with the field shaper disconnected because its connection introduced noise. For a $90 μm \times 90 μm$ X-ray beam at $6 keV$ and a drift field of $100 V {cm}^{- 1}$ , Gaussian fits to the event-centroid distributions gave standard deviations slightly below $100 μm$ in both views. Charge sharing across neighboring strips thus permits centroid reconstruction finer than the $500 μm$ strip pitch. The measured widths include the finite beam size and depend on the event selection; they describe the distribution of reconstructed positions, rather than the size of each ionization cloud. Their variation with energy and field constrains the diffusion and reconstruction models, provided the beamline noise and operating conditions are retained in the comparison.

2.5.3 UV-Light Calibration R&D

During a three-month internship at CEA Saclay, we investigated whether pulsed ultraviolet (UV) light could provide localized primary electrons with a known creation time. Such a source would complement X-ray calibration by allowing charge transport and timing to be studied independently of the photon conversion depth. The concept follows the use of UV-induced photoelectrons in Micromegas-based photocathode detectors such as PICOSEC [84].

We used a pulsed deuterium gas-discharge lamp to illuminate an aluminum photocathode deposited on a UV-transparent $Mg F_{2}$ window. A single-channel Micromegas detector measured the amplified photoelectron charge, with the lamp trigger providing the timing reference. We designed and printed spacers with nominal heights of 3.0, 5.0, 7.5, & 10.0 $mm$ and a height tolerance of $0.1 mm$ to vary the drift distance. Argon–isobutane mixtures flowed through the chamber at $10 L h^{- 1}$ , and an oscilloscope recorded $5000$ pulses per timing point [85].

The arrival time includes electron drift and delays from the lamp, amplification, and electronics. Comparing two distances at the same reduced drift field $𝐸 / 𝑝$ , while keeping the amplification voltage fixed, removes a common delay $𝑡_{0}$ :

𝑡 (𝑑, 𝐸 / 𝑝) = 𝑡_{0} + \frac{𝑑}{𝑣_{𝑑} (𝐸 / 𝑝)}, 𝑣_{𝑑} (𝐸 / 𝑝) = \frac{𝑑_{2} - 𝑑_{1}}{𝑡 (𝑑_{2}, 𝐸 / 𝑝) - 𝑡 (𝑑_{1}, 𝐸 / 𝑝)} .

(2.13)

We interpolated the measured arrival times as functions of field to compare configurations at matching $𝐸 / 𝑝$ . The velocity estimates below use the $3.0 mm$ and $7.5 mm$ spacers. This difference method also avoids using photoemission from the mesh as a second timing reference: that signal was visible at low quencher concentration but weakened as isobutane absorbed the UV light [85].

Figure 2.19 compares the historical estimates for nominal 1% and 5% isobutane with Magboltz calculations. The measured curves reproduce the scale and broad field dependence of the calculated velocity, including its maximum, but the maxima occur at different fields. The comparison therefore demonstrates sensitivity to gas transport without establishing agreement sufficient for an absolute drift calibration.

Figure 2.19: Electron drift velocities from the CEA Saclay UV study, recovered from the vector plots in the presentation of December 20, 2022 [ 85 ]. Black curves are estimates from interpolated pulse times at drift distances of 3.0 mm and 7.5 mm ; blue dashed curves are the corresponding Magboltz calculations. Mixture percentages are nominal mixer settings. The source supplies no uncertainty intervals for these derived curves; no empirical field or velocity correction is applied. — Figure 2.19: Electron drift velocities from the CEA Saclay UV study, recovered from the vector plots in the presentation of December 20, 2022 [85]. Black curves are estimates from interpolated pulse times at drift distances of $3.0 mm$ and $7.5 mm$ ; blue dashed curves are the corresponding `Magboltz` calculations. Mixture percentages are nominal mixer settings. The source supplies no uncertainty intervals for these derived curves; no empirical field or velocity correction is applied.

The gas analyzer readbacks differed from the nominal mixer settings: for example, the reported 1% and 5% settings gave 1.32% and 5.59% isobutane. Mixture equilibration and possible charge accumulation were also identified during the study as effects requiring further tests [85]. The lamp produced large pulse-amplitude fluctuations, limiting its use as a controlled charge source even when arrival times could be measured. These observations motivate a more stable UV source, a characterized photocathode, and controlled gas conditions before quantitative calibration of the BabyIAXO detector. X-ray sources remain the calibration method used for the detector and background analyses in this thesis.

Summary

The prototypes measure X-ray energy and topology through the charge collected on orthogonal strips and the relative timing of their pulses. Stable gas and electrical conditions, monitored with calibration data, determine the response used in the simulations and background analysis.