arXiv subjects

L. Meyer

Publications and source records attributed to L. Meyer.

At least 19 recordsLinked to original sources

arXiv2025

Uncertainty Reasoning with Photonic Bayesian Machines

Artificial intelligence (AI) systems increasingly influence safety-critical aspects of society, from medical diagnosis to autonomous mobility, making uncertainty awareness a central requirement for trustworthy AI. We present a photonic Bayesian machine that leverages the inherent randomness of chaotic light sources to enable uncertainty reasoning within the framework of Bayesian Neural Networks. The analog processor features a 1.28 Tbit/s digital interface compatible with PyTorch, enabling probabilistic convolutions processing within 37.5 ps per convolution. We use the system for simultaneous classification and out-of-domain detection of blood cell microscope images and demonstrate reasoning between aleatoric and epistemic uncertainties. The photonic Bayesian machine removes the bottleneck of pseudo random number generation in digital systems, minimizes the cost of sampling for probabilistic models, and thus enables high-speed trustworthy AI systems.

cs.LG↗

arXiv2025

Description of CRESST-II and CRESST-III pulse shape data

A set of data from 68 cryogenic detectors operated in the CRESST dark matter search experiment between 2013 and 2019 was collected and labeled to train binary classifiers for data cleaning. Here, we describe the data set and how the trained models can be applied to new data. The data and models are available online.

physics.ins-det↗

arXiv2025

Description of CRESST-III lithium aluminate data

Two detector modules with lithium aluminate targets were operated in the CRESST underground setup between February and June 2021. The data collected in this period was used to set the currently strongest cross-section upper limits on the spin-dependent interaction of dark matter (DM) with protons and neutrons for the mass region between 0.25 and 1.5 GeV/c$^2$. The data are available online. In this document, we describe how the data set should be used to reproduce our dark matter results.

hep-ex↗

arXiv2024

First observation of single photons in a CRESST detector and new dark matter exclusion limits

The main goal of the CRESST-III experiment is the direct detection of dark matter particles via their scattering off target nuclei in cryogenic detectors. In this work we present the results of a Silicon-On-Sapphire (SOS) detector with a mass of 0.6$\,$g and an energy threshold of (6.7$\, \pm \,$0.2)$\,$eV with a baseline energy resolution of (1.0$\, \pm \,$0.2)$\,$eV. This allowed for a calibration via the detection of single luminescence photons in the eV-range, which could be observed in CRESST for the first time. We present new exclusion limits on the spin-independent and spin-dependent dark matter-nucleon cross section that extend to dark matter particle masses of less than 100$\,$MeV/c$^{2}$.

astro-ph.CO↗

arXiv2024

DoubleTES detectors to investigate the CRESST low energy background: results from above-ground prototypes

In recent times, the sensitivity of low-mass direct dark matter searches has been limited by unknown low energy backgrounds close to the energy threshold of the experiments known as the low energy excess (LEE). The CRESST experiment utilises advanced cryogenic detectors constructed with different types of crystals equipped with Transition Edge Sensors (TESs) to measure signals of nuclear recoils induced by the scattering of dark matter particles in the detector. In CRESST, this low energy background manifests itself as a steeply rising population of events below 200 eV. A novel detector design named doubleTES using two identical TESs on the target crystal was studied to investigate the hypothesis that the events are sensor-related. We present the first results from two such modules, demonstrating their ability to differentiate between events originating from the crystal's bulk and those occurring in the sensor or in its close proximity.

physics.ins-det↗

arXiv2024

A likelihood framework for cryogenic scintillating calorimeters used in the CRESST dark matter search

Cryogenic scintillating calorimeters are ultrasensitive particle detectors for rare event searches, particularly for the search for dark matter and the measurement of neutrino properties. These detectors are made from scintillating target crystals generating two signals for each particle interaction. The phonon (heat) signal precisely measures the deposited energy independent of the type of interacting particle. The scintillation light signal yields particle discrimination on an event-by-event basis. This paper presents a likelihood framework modeling backgrounds and a potential dark matter signal in the two-dimensional plane spanned by phonon and scintillation light energies. We apply the framework to data from CaWO$_4$-based detectors operated in the CRESST dark matter search. For the first time, a single likelihood framework is used in CRESST to model the data and extract results on dark matter in one step by using a profile likelihood ratio test. Our framework simultaneously fits (neutron) calibration data and physics (background) data and allows combining data from multiple detectors. Although tailored to CaWO$_4$-targets and the CRESST experiment, the framework can easily be expanded to other materials and experiments using scintillating cryogenic calorimeters for dark matter search and neutrino physics.

astro-ph.CO↗

arXiv2023

Optimal operation of cryogenic calorimeters through deep reinforcement learning

Cryogenic phonon detectors with transition-edge sensors achieve the best sensitivity to light dark matter-nucleus scattering in current direct detection dark matter searches. In such devices, the temperature of the thermometer and the bias current in its readout circuit need careful optimization to achieve optimal detector performance. This task is not trivial and is typically done manually by an expert. In our work, we automated the procedure with reinforcement learning in two settings. First, we trained on a simulation of the response of three CRESST detectors used as a virtual reinforcement learning environment. Second, we trained live on the same detectors operated in the CRESST underground setup. In both cases, we were able to optimize a standard detector as fast and with comparable results as human experts. Our method enables the tuning of large-scale cryogenic detector setups with minimal manual interventions.

physics.ins-det↗

arXiv2023

Detector development for the CRESST experiment

Recently low-mass dark matter direct searches have been hindered by a low energy background, drastically reducing the physics reach of the experiments. In the CRESST-III experiment, this signal is characterised by a significant increase of events below 200 eV. As the origin of this background is still unknown, it became necessary to develop new detector designs to reach a better understanding of the observations. Within the CRESST collaboration, three new different detector layouts have been developed and they are presented in this contribution.

physics.ins-det↗

arXiv2023

Light Dark Matter Search Using a Diamond Cryogenic Detector

Diamond operated as a cryogenic calorimeter is an excellent target for direct detection of low-mass dark matter candidates. Following the realization of the first low-threshold cryogenic detector that uses diamond as absorber for astroparticle physics applications, we now present the resulting exclusion limits on the elastic spin-independent interaction cross-section of dark matter with diamond. We measured two 0.175 g CVD (Chemical Vapor Deposition) diamond samples, each instrumented with a W-TES. Thanks to the energy threshold of just 16.8 eV of one of the two detectors, we set exclusion limits on the elastic spin-independent interaction of dark matter particles with carbon nuclei down to dark matter masses as low as 0.122 GeV/c2. This work shows the scientific potential of cryogenic detectors made from diamond and lays the foundation for the use of this material as target for direct detection dark matter experiments.

astro-ph.CO↗

arXiv2023

High-Dimensional Bayesian Likelihood Normalisation for CRESST's Background Model

Using CaWO$_4$ crystals as cryogenic calorimeters, the CRESST experiment searches for nuclear recoils caused by the scattering of potential Dark Matter particles. A reliable identification of a potential signal crucially depends on an accurate background model. In this work we introduce an improved normalisation method for CRESST's model of the electromagnetic backgrounds. Spectral templates, based on Geant4 simulations, are normalised via a Bayesian likelihood fit to experimental background data. Contrary to our previous work, no assumption of partial secular equilibrium is required, which results in a more robust and versatile applicability. Furthermore, considering the correlation between all background components allows us to explain 82.7% of the experimental background within [1 keV, 40 keV], an improvement of 18.6% compared to our previous method.

physics.ins-det↗

arXiv2023

Observation of a low energy nuclear recoil peak in the neutron calibration data of the CRESST-III Experiment

New-generation direct searches for low mass dark matter feature detection thresholds at energies well below 100 eV, much lower than the energies of commonly used X-ray calibration sources. This requires new calibration sources with sub-keV energies. When searching for nuclear recoil signals, the calibration source should ideally cause mono-energetic nuclear recoils in the relevant energy range. Recently, a new calibration method based on the radiative neutron capture on $^{182}$W with subsequent de-excitation via single $\gamma$-emission leading to a nuclear recoil peak at 112 eV was proposed. The CRESST-III dark matter search operated several CaWO$_{4}$-based detector modules with detection thresholds below 100 eV in the past years. We report the observation of a peak around the expected energy of 112 eV in the data of three different detector modules recorded while irradiated with neutrons from different AmBe calibration sources. We compare the properties of the observed peaks with Geant-4 simulations and assess the prospects of using this for the energy calibration of CRESST-III detectors.

physics.ins-det↗

arXiv2022

Results on sub-GeV Dark Matter from a 10 eV Threshold CRESST-III Silicon Detector

We present limits on the spin-independent interaction cross section of dark matter particles with silicon nuclei, derived from data taken with a cryogenic calorimeter with 0.35 g target mass operated in the CRESST-III experiment. A baseline nuclear recoil energy resolution of $(1.36\pm 0.05)$ eV$_{\text{nr}}$, currently the lowest reported for macroscopic particle detectors, and a corresponding energy threshold of $(10.0\pm 0.2)$ eV$_{\text{nr}}$ have been achieved, improving the sensitivity to light dark matter particles with masses below 160 MeV/c$^2$ by a factor of up to 20 compared to previous results. We characterize the observed low energy excess, and we exclude noise triggers and radioactive contaminations on the crystal surfaces as dominant contributions.

astro-ph.CO↗

arXiv2022

Towards an automated data cleaning with deep learning in CRESST

The CRESST experiment employs cryogenic calorimeters for the sensitive measurement of nuclear recoils induced by dark matter particles. The recorded signals need to undergo a careful cleaning process to avoid wrongly reconstructed recoil energies caused by pile-up and read-out artefacts. We frame this process as a time series classification task and propose to automate it with neural networks. With a data set of over one million labeled records from 68 detectors, recorded between 2013 and 2019 by CRESST, we test the capability of four commonly used neural network architectures to learn the data cleaning task. Our best performing model achieves a balanced accuracy of 0.932 on our test set. We show on an exemplary detector that about half of the wrongly predicted events are in fact wrongly labeled events, and a large share of the remaining ones have a context-dependent ground truth. We furthermore evaluate the recall and selectivity of our classifiers with simulated data. The results confirm that the trained classifiers are well suited for the data cleaning task.

physics.ins-det↗

arXiv2022

Latest observations on the low energy excess in CRESST-III

The CRESST experiment observes an unexplained excess of events at low energies. In the current CRESST-III data-taking campaign we are operating detector modules with different designs to narrow down the possible explanations. In this work, we show first observations of the ongoing measurement, focusing on the comparison of time, energy and temperature dependence of the excess in several detectors. These exclude dark matter, radioactive backgrounds and intrinsic sources related to the crystal bulk as a major contribution.

astro-ph.CO↗

arXiv2022

Testing spin-dependent dark matter interactions with lithium aluminate targets in CRESST-III

In the past decades, numerous experiments have emerged to unveil the nature of dark matter, one of the most discussed open questions in modern particle physics. Among them, the CRESST experiment, located at the Laboratori Nazionali del Gran Sasso, operates scintillating crystals as cryogenic phonon detectors. In this work, we present first results from the operation of two detector modules which both have 10.46 g LiAlO$_2$ targets in CRESST-III. The lithium contents in the crystal are $^6$Li, with an odd number of protons and neutrons, and $^7$Li, with an odd number of protons. By considering both isotopes of lithium and $^{27}$Al, we set the currently strongest cross section upper limits on spin-dependent interaction of dark matter with protons and neutrons for the mass region between 0.25 and 1.5 GeV/c$^2$.

astro-ph.CO↗

arXiv2016

An Improved Distance and Mass Estimate for Sgr A* from a Multistar Orbit Analysis

We present new, more precise measurements of the mass and distance of our Galaxy's central supermassive black hole, Sgr A*. These results stem from a new analysis that more than doubles the time baseline for astrometry of faint stars orbiting Sgr A*, combining two decades of speckle imaging and adaptive optics data. Specifically, we improve our analysis of the speckle images by using information about a star's orbit from the deep adaptive optics data (2005 - 2013) to inform the search for the star in the speckle years (1995 - 2005). When this new analysis technique is combined with the first complete re-reduction of Keck Galactic Center speckle images using speckle holography, we are able to track the short-period star S0-38 (K-band magnitude = 17, orbital period = 19 years) through the speckle years. We use the kinematic measurements from speckle holography and adaptive optics to estimate the orbits of S0-38 and S0-2 and thereby improve our constraints of the mass ($M_{bh}$) and distance ($R_o$) of Sgr A*: $M_{bh} = 4.02\pm0.16\pm0.04\times10^6~M_{\odot}$ and $7.86\pm0.14\pm0.04$ kpc. The uncertainties in $M_{bh}$ and $R_o$ as determined by the combined orbital fit of S0-2 and S0-38 are improved by a factor of 2 and 2.5, respectively, compared to an orbital fit of S0-2 alone and a factor of $\sim$2.5 compared to previous results from stellar orbits. This analysis also limits the extended dark mass within 0.01 pc to less than $0.13\times10^{6}~M_{\odot}$ at 99.7% confidence, a factor of 3 lower compared to prior work.

astro-ph.GA↗

arXiv2014

The nuclear cluster of the Milky Way: Our primary testbed for the interaction of a dense star cluster with a massive black hole

This article intends to provide a concise overview, from an observational point-of-view, of the current state of our knowledge of the most relevant properties of the Milky Way's nuclear star cluster (MWNSC). The MWNSC appears to be a typical specimen of nuclear star clusters, which are found at the centers of the majority of all types of galaxies. Nuclear clusters represent the densest and most massive stellar systems in the present-day Universe and frequently coexist with central massive black holes. They are therefore of prime interest for studying stellar dynamics and the MWNSC is the only one that allows us to obtain data on milli-parsec scales. After discussing the main observational constraints, we start with a description of the overall structure and kinematics of the MWNSC, then focus on a comparison to extragalactic systems, summarize the properties of the young, massive stars in the immediate environment of the Milky Way's central black hole, Sagittarius\,A*, and finally focus on the dynamics of stars orbiting the black hole at distances of a few to a few tens of milli parsecs.

astro-ph.GA↗

arXiv2014

Spitzer/IRAC Observations of the Variability of Sgr A* and the Object G2 at 4.5 microns

We present the first detection from the Spitzer Space Telescope of 4.5 micron variability from Sgr A*, the emitting source associated with the Milky Way's central black hole. The >23 hour continuous light curve was obtained with the IRAC instrument in 2013 December. The result characterizes the variability of Sgr A* prior to the closest approach of the G2 object, a putative infalling gas cloud that orbits close to Sgr A*. The high stellar density at the location of Sgr A* produces a background of ~250 mJy at 4.5 microns in each pixel with a large pixel-to-pixel gradient, but the light curve for the highly variable Sgr A* source was successfully measured by modeling and removing the variations due to pointing wobble. The observed flux densities range from the noise level of ~0.7 mJy rms in a 6.4-s measurement to ~10 mJy. Emission was seen above the noise level ~34% of the time. The light curve characteristics, including the flux density distribution and structure function, are consistent with those previously derived at shorter infrared wavelengths. We see no evidence in the light curve for activity attributable to the G2 interaction at the observing epoch, ~100 days before the expected G2 periapsis passage. The IRAC light curve is more than a factor of two longer than any previous infrared observation, improving constraints on the timescale of the break in the power spectral distribution of Sgr A* flux densities. The data favor the longer of the two previously published values for the timescale.

astro-ph.HE↗