Custom-Built Beam Profiler

• Custom-built beam profiler is an instrument that accurately measures charged particle and photon beams using tailored detection methods and specialized hardware.
• It integrates refined optical systems, calibrated detection elements, and rapid data acquisition to achieve sub-20 μm spatial resolution and high temporal performance.
• Advanced calibration techniques and machine-learning algorithms enhance real-time beam profile reconstruction for improved accelerator and medical applications.

A custom-built beam profiler is an instrument or assembly purpose-designed for quantitative measurement of charged particle or photon beam profiles, encompassing particle accelerators (ions, electrons, protons), synchrotron light, medical beams, and high-intensity lasers. The term refers to solutions where commercial limitations, unique experimental constraints, or performance demands necessitate the selection, integration, calibration, or innovation of hardware and analysis methodology tailored for a specific application. Customization may address spatial or temporal resolution, invasiveness, spectral sensitivity, dynamic range, real-time data analysis, robustness in radiation environments, or integration with accelerator controls.

1. Detection Principles and Device Architectures

Two broad classes of detection interaction dominate: interception (measurement via interaction with a “probe” element) and non-intercepting (inference from secondary signals). Intercepting profilers include scintillator-based screens, OTR foils, wire grids, fiber scanners, plastic scintillators, and waveguide arrays. Non-intercepting approaches encompass electromagnetic field measurement and machine learning–based profile inference.

Major Detection Modalities in Custom-Built Beam Profilers

Detection Principle	Implementation Example	Primary Application Domain
Radiative Converter Screens	YAG:Ce, OTR foils (Lumpkin et al., 2012)	Electron/proton accelerators, linacs
Optical Interference/Imaging	Double-slit interferometers (Wang et al., 2014)	Synchrotron light, storage rings
Ionization or Current Grids	Metallic wire grids (Bouquerel et al., 2 Jul 2024)	Low-energy ion sources, electron guns
Scintillating Fiber Arrays	Plastic Sci-Fi, SiPM readout (Kino et al., 28 May 2024)	GeV photon lines, medical beamlines
Plastic Scintillator + CIS	Contact image sensors (Hsiao et al., 2019)	Proton therapy and QA monitoring
Microstructured Scintillators	Molded resin waveguides (Leccese et al., 2023)	Proton/heavy ion accelerators
Machine-Learning Analysis	BPM stripline with profile reconstruction (Omarov et al., 2020)	Non-destructive, real-time storage rings
Optical Fiber Scanning	Fiber probe for vacuum/UV/high power (Brand et al., 2019)	Laser diagnostics, UHV, confined spaces
Imaging and Computer Vision	CMOS/CCD, PCA cleanup (Jachinowski et al., 2022)	Atom interferometry, general optics

All designs are highly influenced by the target particle/beam energy, required resolution, temporal constraints, and operational tolerance for beam disturbance.

2. Key Components and Customization Parameters

Custom-built beam profilers are assembled by integrating and optimizing several primary subcomponents, tuned to application requirements:

Converter Screen and Detection Element

• Scintillator screens (YAG:Ce, LYSO:Ce, BC-408) convert beam energy into visible photons; thickness and orientation dictate spatial resolution and light yield (Lumpkin et al., 2012, Hsiao et al., 2019).
• OTR foils provide prompt optical emission for high-brightness electron or proton bunches, optimal for minimal space charge regimes (Lumpkin et al., 2012).
• Microstructured or fiber-based detectors allow channel multiplexing, robust light guidance, and minimal mechanical footprint, with waveguide cross-section, pitch, and coupling engineered for required resolution (Leccese et al., 2023, Kino et al., 28 May 2024, Nesteruk et al., 2017).

Optical Extraction and Transport

• Projection optics (zoom or fixed/focal length lenses), mirrors (notably a 45° geometry), and virtual targets are selected for RMS point-spread minimization (sub-10 μm for small FOVs).
• Devices may utilize polarization filters, beam splitters for calibration or simultaneous diagnostics (e.g., MTF/ERF or streak-camera channels) (Lumpkin et al., 2012, Wang et al., 2014).

Readout and Data Acquisition

• Imaging via cameras (CCD, CMOS, CIS, Pi NoIR) with pixel sizes from 1.1 μm upward, signal conditioning (neutral density filters, photodiodes), and digitization with appropriate ADC resolution and real-time data streaming (Keaveney, 2018, Hsiao et al., 2019, Kino et al., 28 May 2024).
• Newer systems utilize fast (ns-range) streaming TDC, SiTCP Ethernet, microcontrollers for onboard control, or triggerless architecture for MHz-scale rate handling (Kino et al., 28 May 2024, Leccese et al., 2023).

Motion and Mechanical Assembly

• Translation stages (linear, rotary, motorized) are applied for 1D or 2D profiling, automatic focus determination, or beam overlap studies; grid or wire arrays on precision frames enable systematic spatial mapping, with fine pitch or motorized drive (Keaveney, 2018, Bouquerel et al., 2 Jul 2024).

Signal Processing and Calibration

• Onboard calibration using virtual targets (USAF charts), UV LEDs, or built-in phantom signals mitigate drift and uniformity nonidealities (Lumpkin et al., 2012, Leccese et al., 2023).
• Advanced image-processing (PCA, machine vision, ML-based mode decomposition) enhances SNR and discriminates stationary or systematic backgrounds (Jachinowski et al., 2022, Omarov et al., 2020, Bekerman et al., 2019).

3. Representative Profiling Techniques and Analysis

The core measurement is an inference of the beam’s true spatial distribution, I(x, y), from an instrumentally convoluted observation O(x, y), where O = I * K (with K the system response function). Practical analysis entails:

3.1 Direct Imaging

• Used for moderate- to large-scale profiles (>50 μm), with screen/camera system resolution characterized via MTF or edge response. RMS instrumental broadening is subtracted quadratically: $$\sigma_\text{meas}^2 = \sigma_\text{beam}^2 + \sigma_\text{screen}^2 + \sigma_\text{optics}^2$$ (Lumpkin et al., 2012).

3.2 Interferometric and Coherence-Based Methods

• For sub-100 μm beams, double-slit interferometry measures the visibility, y, and derives beam size via coherence theory (van Cittert–Zernike theorem):

$\sigma_x = \frac{\lambda L}{\pi D}\sqrt{-\ln y}$

• T-polarization and valley-to-peak intensity methods address very small vertical beam dimensions (Wang et al., 2014).

3.3 Fiber and Microstructured Scintillator Profilers

• Position is encoded via fiber channel or waveguide number; total intensity per channel maps the transverse profile.
• Overall detection efficiency is

$$\eta_\text{total} = \eta_\text{Scint} \cdot \eta_\text{Waveguide} \cdot \eta_\text{Air} \cdot \eta_\text{PD}$$

with each efficiency factor determined via simulation and calibration (Leccese et al., 2023).

3.4 Non-Interceptive Electromagnetic Reconstruction

• Stripline-type beam position monitors, combined with genetic algorithms and signal comparison (mean squared error plus exponential size penalty), reconstruct distorted and higher-order beam profiles from button electrode responses, applying the expansion:

$$J_\text{image}(r,\phi,a,\theta) = \frac{I(r,\phi)}{2\pi a}\left[1+2\sum_{k=1}^{\infty}\left(\frac{r}{a}\right)^k\cos k(\theta-\phi)\right]$$

(Omarov et al., 2020).

4. Performance Characteristics and Error Budgeting

• Spatial resolution below 10–20 μm RMS is common in modern custom stations, constrained by optical system quality, screen properties, and detector pixellation (Lumpkin et al., 2012, Hsiao et al., 2019, Leccese et al., 2023).
• Temporal resolution can reach 1 MHz (mrines-level) or higher using fast CIS, SiPM arrays, or streaming TDC (Kino et al., 28 May 2024, Leccese et al., 2023).
• For each measured profile, uncertainties are systematically budgeted:
  • Instrumental response contributions (screen blur, optics),
  • Statistical error (photon/electron counting),
  • Calibration drift and systematic shifts (via virtual targets or onboard LEDs),
  • Effects of intensity imbalance, depth of field, jitter (phase error influence on interferometric visibilities: $\Delta\phi = 2\pi DA_x/\lambda$), and background (Wang et al., 2014).

Most systems benchmark accuracy against theoretical predictions or reference commercial instruments; disparities typically arise from non-idealities (residual resin in microstructured scintillators, finite fiber pitch, misalignments, or convolution kernel deformation).

5. Applications in Scientific and Medical Accelerator Environments

Custom-built profilers enable:

• High-precision characterization of ultrarelativistic electron/photon/proton beams for accelerator R&D, FELs, medical therapy, and next-generation collider studies (Leccese et al., 2023, Kino et al., 28 May 2024, Lumpkin et al., 2012).
• Continuous real-time monitoring of high-intensity beams (MHz regime, >10^8 pps) using non-invasive approaches, crucial for Main Injector–class or medical accelerator QA (Thurman-Keup et al., 2015, Hsiao et al., 2019).
• Support for beam dynamics studies (emittance, Twiss parameters, energy spread) and machine learning–aided online adjustment and optimization (with real-time simulation input for codes such as MAD-X) (Nesteruk et al., 2017).
• Resolution of low-charge, small spot-size challenges (down to 15 pC in photoinjectors), assessment of aberrations and wavefront quality in atom interferometry or quantum sensing applications (Lumpkin et al., 2012, Jachinowski et al., 2022).

6. Design Evolution, Innovations, and Future Perspectives

Recent progress in custom-built beam profiler design includes:

• Adoption of machine vision and PCA/ML techniques for robust denoising, profile reconstruction in the presence of systematics, and phase retrieval–free spatial mode classification (Jachinowski et al., 2022, Bekerman et al., 2019).
• Use of advanced materials and microfabrication (photolithography, DRIE, PDMS molding, microstructured resin) for dense fiber arrays or waveguide-based scintillator plates (Leccese et al., 2023).
• Engineering of radiation-hardened, compact, and easily replaceable active areas for environments with high cumulative dose inputs (Hsiao et al., 2019, Leccese et al., 2023).
• Scalable and modular DAQ integrating FPGA-based streaming TDC and SiTCP, supporting integration into facility-wide controls and real-time feedback (Kino et al., 28 May 2024).
• Synergy between direct imaging and non-intercepting, model-based inference for minimally disruptive, high-throughput profiling, with applications spanning accelerator commissioning, patient-specific medical therapy QA, materials processing, and quantum information transfer.

Future developments aim to miniaturize detector elements, increase rates, close systematic error sources, and leverage emerging data analysis techniques for enhanced automation, precision, and functional scope.