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DOE OSTI2025

Characterization of Lateral Amorphous Selenium Photodetectors for Low-Photon and VUV Detection at Cryogenic Temperatures

The performance of amorphous selenium (a-Se) as a cryogenic photodetector material is evaluated through a series of experiments using laterally structured devices operated in a custom optical test stand. These studies investigate the response of a-Se detectors to low-photon fluxes at high electric fields near avalanche conditions, the linearity of the photoconductive response over a wide dynamic range and the direct detection of narrowband 130 nm vacuum ultraviolet (VUV) illumination. At 87 K, matched-filter analysis shows reliable single-shot detection with efficiencies greater than or equal to 80 percent and area under the curve (AUC) greater than or equal to 0.85 using as few as approximately 6800 incident 401 nm photons, corresponding to approximately 3400 photons within field-active regions after accounting for geometric constraints. Measurements are performed at cryogenic temperatures using calibrated photon fluxes derived from a silicon photomultiplier reference and a characterized optical filter stack. Additional experiments using a tellurium-doped a-Se (a-SeTe) device explore the material's behavior under identical test conditions and demonstrate that avalanche is achievable in a-SeTe at cryogenic temperatures. The results demonstrate reproducible low-noise operation, VUV sensitivity and field-dependent gain behavior in a lateral a-Se architecture, representing the first reported observation of avalanche multiplication in laterally structured a-Se and a-SeTe devices at cryogenic temperatures. These findings support the potential integration of laterally structured a-Se devices into next-generation pixelated liquid-argon time projection chambers (TPCs) requiring scalable, high-field-compatible photon detection systems.

FOS: Physical sciences↗

DOE OSTI2020

An Improved Measurement of the Secondary Cosmic Microwave Background Anisotropies from the SPT-SZ + SPTpol Surveys

We report new measurements of millimeter-wave power spectra in the angular multipole range $2000 \le \ell \le 11,000$ (angular scales $5^\prime \gtrsim \theta \gtrsim 1^\prime$). By adding 95 and 150\,GHz data from the low-noise 500 deg$^2$ SPTpol survey to the SPT-SZ three-frequency 2540 deg$^2$ survey, we substantially reduce the uncertainties in these bands. These power spectra include contributions from the primary cosmic microwave background, cosmic infrared background, radio galaxies, and thermal and kinematic Sunyaev-Zel'dovich (SZ) effects. The data favor a thermal SZ (tSZ) power at 143\,GHz of $D^{\rm tSZ}_{3000} = 3.42 \pm 0.54~ \mu {\rm K}^2$ and a kinematic SZ (kSZ) power of $D^{\rm kSZ}_{3000} = 3.0 \pm 1.0~ \mu {\rm K}^2$. This is the first measurement of kSZ power at $\ge 3\,\sigma$. We study the implications of the measured kSZ power for the epoch of reionization, finding the duration of reionization to be $\Delta z_{re} = 1.0^{+1.6}_{-0.7}$ ($\Delta z_{re}< 4.1$ at 95% confidence), when combined with our previously published tSZ bispectrum measurement.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Optical encoder devices and systems

Devices, systems and methods for encoding information using optical components are described. Information associated with a first optical signal (e.g., an optical pump) is encoded onto the phase of a second optical signal (e.g., an optical probe) using cross phase modulation (XPM) in a non-linear optical medium. The optical signals are multiplexed together into the nonlinear optical medium. The probe experiences a modified index of refraction as it propagates through the medium and thus accumulates a phase change proportional to the intensity of the pump. The disclosed devices can be incorporated into larger components and systems for various applications such as scientific diagnostics, radar, remote sensing, wireless communications, and quantum computing that can benefit from encoding and generation of low noise, high resolution signals. Examples of the encoded information includes intrinsic noise from the optical source, or others signals of interest, such as electrical, optical, X-ray, or high-energy particle signals.

Buckley, Brandon Walter↗

DOE OSTI2021

3D superconducting radio-frequency resonators for quantum computing

Superconducting radiofrequency (SRF) technology is being used not only in discovery science programs and basic research but also for several applications that benefit society more directly. The advantage of superconducting resonators over those made of normal-conducting metal is their ability to store electromagnetic energy with much lower dissipation. The high quality factor and longer dissipation time provided by these superconducting resonators can deliver superior performance. Currently, the quantum processing architecture uses resonators and interconnecting circuits operating in the microwave regime with superconducting strip-line technology and low noise electronic devices for switching and communication. The performance of these devices can be enhanced by embedding them in 3D SRF cavity resonators to prolong the coherence time, which improves the utility of the device by reducing error rates and allowing more manipulations (calculations) before the quantum state decays. In this presentation, I will review the current technology and progress towards the three dimensional SRF cavities to enhance the coherence time.

Dhakal, Pashupati↗

DOE OSTI2023

Optical encoder devices and systems

Buckley, Brandon Walter↗

DOE OSTI2023

X-ray Parametric Down Conversion at the APS Synchrotron

We present measurements of X-ray Parametric Down Conversion at the Advanced Photon Source synchrotron facility. We use an incoming pump beam at 22 keV to observe the simultaneous, elastic emission of down-converted photon pairs generated in a diamond crystal. The pairs are detected using high count rate silicon drift detectors with low noise. Production by down-conversion is confirmed by measuring time-energy correlations in the detector signal, where photon pairs within an energy window ranging from 10 to 12 keV are only observed at short time differences. By systematically varying the crystal misalignment and detector positions, we obtain results that are consistent with the constant total of the down-converted signal.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

SERAPH: Wavelike Dark Matter Searches with SRF Cavities

Haloscopes consisting of a microwave cavity with a high quality factor (Q) connected to low-noise electronics have been deployed to detect wavelike axions and dark photons. But the dark matter mass is unknown, so haloscopes must be tunable to search through the photon coupling vs. mass parameter space. Therefore, the scan rate for haloscope experiments is a crucial figure of merit and is proportional to the cavity’s quality factor. State-of-the-art experiments like ADMX currently use copper cavities with 𝑄∼80000. However, implementing superconducting cavities with 𝑄∼1010 can increase the instantaneous scan rate by possibly a factor of 105.This presentation will report progress on the SERAPH experiment, a family of superconducting haloscopes being developed by the Superconducting Quantum Materials and Systems (SQMS) Center. In this presentation, I will first discuss the principles behind operating a haloscope whose bandwidth is much narrower than the dark matter halo energy distribution. I will then describe the first SERAPH experiments implementing a 1.3 GHz Niobium cavity with an ultra-high quality factor (Q~1010) that has achieved the best sensitivity and deepest exclusion to wavelike dark photon dark matter by almost an order of magnitude. Next, I will discuss progress on the next phase of SERAPH, which will search dark photon dark matter using a widely-tunable SRF cavity (4-7 GHz). I will finally describe plans for subsequent SERAPH experiments to search for dark photons and axions with tunable SRF cavities tolerant to multi-Tesla magnetic fields and quantum sensors that subvert the Standard Quantum Limit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Simulation based inference with domain adaptation for strong gravitational lensing

Simulation based inference leverages machine learning to carry out Bayesian inference in systems with intractable likelihoods. However, transitioning a network trained on simulated data to real data runs the risk of encountering domain shift, leading to performance losses. We attempt to implement domain adaptation into the sbi neural posterior estimation framework using the Maximum Mean Discrepancy as an additional network loss, using masked autoregressive fow (MAF) as our density estimator. We test the network on a set of 400,000 simulated strong gravitational lensing images generated using deeplenstronomy. The source domain is defined as low noise whereas the target domain has a noise profile sampled from experimentally derived DES survey conditions. We find that SBI appears robust against small changes in the data with similar performance on source and target. Moreover, while DA does lead to performance improvements, they are marginal at 6% less inference error.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

DarkNESS: Characterization of Space Multi-Chip Module Skipper-CCDs and Readout Electronics

The DarkNESS mission has the goal of deploying a 6U CubeSat fitted with an array of skipper-CCDs in Low Earth Orbit (~400 km). The new instrument will take measurements of diffuse x-rays and look for signatures of dark matter decay in the spectrum. DarkNESS will also perform a direct search for strongly interacting sub-GeV dark matter in regions of the parameter space not accessible to ground based experiments [1]. Skipper-CCDs allow for low-noise astronomical observations which can extend the discovery reach for direct dark matter search experiments. This paper will discuss the laboratory characterization of the two key components of the scientific payload: the space Multi-Chip Module (sMCM), and their readout electronics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Refinement and Modeling of a Blackbody-Based Calibration Method in the InfraBREAD Detector

The Broadband Reflector Experiment for Axion Detection (BREAD) is an ongoing collaboration searching for the conversion of yet undiscovered axion-like dark matter particles to photons in the presence of a magnetic field. InfraBREAD, an experiment of BREAD, uses a superconducting nanowire single photon detector (SNSPD), a high-efficiency and low-noise device, to specifically detect infrared-range photons produced by $\mathcal{O}$(eV) axion-like particles. The unique BREAD reflector setup allows for the focusing of converted signal photons to a 1mm $\times$ 1mm SNSPD. However, when the detector is cooled to cryogenic temperatures during operation, uneven thermal contraction of reflector components may lead to a small shift in the location of the focal spot. A novel calibration method using blackbody radiation is proposed to locate the true focal spot of the detector \textit{in situ}. Through ray tracing simulations done in FRED Optical Engineering Software, this method is demonstrated to locate the focus to within $\SI{50}{\micro\metre}$ in the $z$ dimension.

Rao, Shardul↗

DOE OSTI2024

Modeling and Proof-of-Concept of a Blackbody-Based Calibration Method in the InfraBREAD Detector

The Broadband Reflector Experiment for Axion Detection (BREAD) is an ongoing collaboration searching for the conversion of yet undiscovered axion-like dark matter particles to photons in the presence of a magnetic field. InfraBREAD, a pilot experiment realization of BREAD, uses a superconducting nanowire single photon detector (SNSPD), a high-efficiency and low-noise device, to specifically detect infrared-range photons produced by $\mathcal{O}$(eV) axion-like particles. The unique BREAD coaxial reflector setup allows for the focusing of converted signal photons to a 1mm $\times$ 1mm SNSPD. However, when the detector is cooled to cryogenic temperatures during operation, uneven thermal contraction of reflector components may lead to a small shift in the location of the focal spot. A novel calibration method using blackbody radiation is proposed to locate the true focal spot of the detector \textit{in situ}. Through ray tracing simulations done in FRED Optical Engineering Software, this method is demonstrated to locate the focus to within $\SI{50}{\micro\metre}$ in the axial dimension. Additionally, it is demonstrated that the blackbody photon source used in this calibration must be at a temperature of at least $\SI{15}{\kelvin}$ to $\SI{40}{\kelvin}$, depending on the sensitivity of the SNSPD.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Automating Sensor Characterization with Bayesian Optimization

The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert's time. In this work, we present a novel technique for automated sensor calibration that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.

Cuevas-Zepeda, Julian [Chicago U., KICP; Chicago U↗

DOE OSTI2025

Automating Testing of DUNE Electronics via a Finite State Machine

The Deep Underground Neutrino Experiment (DUNE) is a flagship international collaboration designed to study neutrinos—tiny, nearly massless particles that may hold answers to fundamental questions about the Universe. Fermilab’s Robotic Test Stand (RTS) plays a critical role in ensuring the quality of approximately 50,000 Application-Specific Integrated Circuit (ASIC) chips that will be used in DUNE’s massive liquid argon detectors. These electronics will be inside the cryostat; therefore, they will need to have a high yield of working chips and low noise. To improve the automation and reliability of the RTS, this project focused on designing and implementing a Python-based finite state machine (FSM) to manage chip handling workflows. The FSM was developed as a modular software framework to coordinate robotic arm movements, manage chip tray positions, and monitor system states during testing. Key features include robust error handling routines, a pause/resume system for safe mid-cycle interruptions, and a simulation mode for iterative testing without hardware dependencies. The system was designed to prepare for seamless integration with RTS hardware components such as the robotic arm and vision system. This integration will streamline collaboration and enable efficient deployment of updates across the six institutions performing testing. The outcomes of this internship contribute to Fermilab’s mission to advance high-energy physics and support the DOE’s national goals by directly improving the testing of equipment to be used in DUNE. The project also provided valuable experience in software design and contributing to the success of DUNE.

Kang, Caleb [Fermilab]↗

DOE OSTI2026

MAS-CCD: New technique for measuring low-level charge content based on the multiple amplifier architecture

Low-noise detectors are a key technology for the next generation of astronomical instruments aimed at spectroscopy of faint objects and the search for exoplanets. In this context, the multiple-amplifier sensing charge-coupled device (MAS-CCD) emerges as a promising technology for future scientific instruments. A critical parameter affecting the performance of these devices is spurious charge, produced by the clocking of the gates. Its measurement is typically challenging with existing methods. In practice, the optimization of this parameter often relies on empirical procedures that require significant time and careful consideration of the trade-off with full-well capacity. In this work, we present a new technique to estimate spurious charge based on covariance analysis of the output amplifiers of the MAS-CCD, which measures the same charge packet in different amplifiers at different times. The method enables fast and precise measurements of spurious charge under operating conditions where conventional approaches are difficult to apply. We develop the theoretical framework of the method and validate the model through simulations. The results demonstrate the feasibility of this approach and suggest that it could serve as a basis for reliable large-scale characterization of sensor performance.

Gamero, Miqueas E. [Buenos Aires, CONICET; Fermila↗

DOE OSTI2026

Alcock-Paczynski Blinding Scheme for the Ly-$α$ Forest Analysis

We present and validate a blinding method for the Lyman-$α$ (Ly$α$) forest analysis based on a modification of the Alcock-Paczynski test. In order to hide the background expansion history, the method employs a geometrical shift of each quasar (QSO) forest in wavelength space, once the quasar continuum has been fitted and the fluctuation field is extracted. The redshift positions for the QSO sample are also changed in a consistent manner. We show that the method remains effective when applied to real data, where contamination from metals and Lyman-$β$ is intrinsically mixed with the Lyman-$α$ forest. This limitation is primarily visible in the 1D correlation function, where other blinding strategies can mitigate the effect. To assess its effectiveness, the prescription is tested against a series of datasets of increasing complexity: from idealized low-noise mocks, to realistic DESI year one synthetic datasets, and finally to data from DESI first data release (DR1), using both the auto (Ly$α\times$Ly$α$) and cross (Ly$α\times$ QSO) correlations. We find that the method robustly shifts the BAO peak position from the 3D correlation functions to the expected value for cosmology changes of around 5% in the matter content, without altering the shape of the posteriors in the model parameters. In conclusion, this catalog-level blinding strategy is a viable method for cosmological inference with the Lyman-$α$ forest, particularly if a cross-analysis with other tracers using the same blinding strategy is pursued.

Perez-Sanchez, G. [Guanajuato U.] (ORCID:000900096↗

DOE OSTI2021

Low-Frequency Electronic Noise in Quasi-2D van der Waals Antiferromagnetic Semiconductor FePS 3 —Signatures of Phase Transitions

Here, low-frequency current fluctuations, i.e., noise, in the quasi-2D van der Waals antiferromagnetic semiconductor FePS 3 with the electronic bandgap of 1.5 eV is investigated. The electrical and noise characteristics of the p-type, highly resistive, thin films of FePS 3 are measured at different temperatures. The noise spectral density is of the 1/f-type over most of the examined temperature range but reveals well-defined Lorentzian bulges, and increases strongly near the Néel temperature T N =118 K (f is the frequency). Intriguingly, the noise spectral density attains its minimum at temperature T≈200 K, which is attributed to an interplay of two opposite trends in noise scaling—one for semiconductors and another for materials with the phase transitions. The Lorentzian corner frequencies reveal unusual dependence on temperature and bias voltage, suggesting that their origin is different from the generation—recombination noise in conventional semiconductors. The obtained results are important for proposed applications of antiferromagnetic semiconductors in spintronic devices. They also attest to the power of the noise spectroscopy for monitoring various phase transitions.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Low Offset and Noise in High Biased GaN 2DEG Hall-Effect Plates Investigated With Infrared Microscopy

This article presents GaN two-dimensional electron gas (2DEG) Hall plates with low residual offset and noise at 3 V input bias. We studied devices made from three consecutive fabrication generations through current spinning offset measurements in a zero-field chamber. When operated above 1 V, the first-generation devices charted high residual offsets >1 mT. We reduced these residual offsets by three orders of magnitude in later device generations. Two experiments were performed to confirm the improvements. First, the GaN 2DEG Hall-effect plates were measured with infrared microscopy during current spinning to investigate current crowding and Joule heating. The low offset devices had minimal thermal gradients while the high offset devices had large thermal variations during current spinning. Second, zero-field current spinning was used to compare GaN 2DEG Hall-effect plates against typical commercial silicon Hall-effect plates. The Si devices had residual offsets >10μT biased at 3 V and AlGaN/GaN devices had residual offset <4 μT at 3 V, and an InAlN/GaN devices operated at 2 V had a residual offset <4 μT . Thus, for the first time, GaN 2DEG Hall-effect plates were shown to operate with high bias with low offsets and noise, which enables high fidelity sensing applications in extreme environments.

2DEG↗

DOE OSTI2021

Boosting the signal-to-noise of low-field MRI with deep learning image reconstruction

Recent years have seen a resurgence of interest in inexpensive low magnetic field (< 0.3 T) MRI systems mainly due to advances in magnet, coil and gradient set designs. Most of these advances have focused on improving hardware and signal acquisition strategies, and far less on the use of advanced image reconstruction methods to improve attainable image quality at low field. We describe here the use of our end-to-end deep neural network approach (AUTOMAP) to improve the image quality of highly noise-corrupted low-field MRI data. We compare the performance of this approach to two additional state-of-the-art denoising pipelines. We find that AUTOMAP improves image reconstruction of data acquired on two very different low-field MRI systems: human brain data acquired at 6.5 mT, and plant root data acquired at 47 mT, demonstrating SNR gains above Fourier reconstruction by factors of 1.5- to 4.5-fold, and 3-fold, respectively. In these applications, AUTOMAP outperformed two different contemporary image-based denoising algorithms, and suppressed noise-like spike artifacts in the reconstructed images. The impact of domain-specific training corpora on the reconstruction performance is discussed. The AUTOMAP approach to image reconstruction will enable significant image quality improvements at low-field, especially in highly noise-corrupted environments.

42 ENGINEERING↗