arXiv subjects

Daniel Schmidt

Publications and source records attributed to Daniel Schmidt.

At least 19 recordsLinked to original sources

arXiv2026

Nonlinear Elasticity at the Damage Threshold of Semiconductor Nanocrystals

The nonlinear photoacoustic response of indium phosphide nanocrystals on silicon nanotip arrays is investigated using time-resolved optical pump-probe spectroscopy and synchrotron-based X-ray diffraction. Femtosecond laser excitation triggers low-frequency and high-frequency radial breathing modes of the nanocrystals at 8 GHz and 10.3 GHz, respectively. At excitation fluences above 3 mJ/cm^2, nonlinear frequency mixing occurs, including sum- and difference-frequency generation, indicative of strain-induced nonlinear elasticity. A higher-order extension of Hooke's law models the fluence-dependent spectral response and yields a physically valid elastic energy potential. Ex-situ energy-dispersive X-ray spectroscopy reveals a correlation between nanocrystal oxidation and the emergence of nonlinear acoustic modes. Time-resolved X-ray diffraction confirms the nanocrystals as the origin of the low-frequency modes and supports the hypothesis of acoustic decoupling from the substrate. These findings provide insight into the mechanical limits of semiconductor nanostructures under intense optical excitation and suggest new pathways for material characterization and optomechanical control at the nanoscale. The results advance the understanding of nonlinear phonon dynamics in nanocrystals and highlight their potential for integration into next-generation photonic and quantum devices.

cond-mat.mtrl-sci↗

arXiv2026

Design of a mission to measure the shape and substructure of the 511 keV gamma-ray line from the center of the Milky Way

The 511 keV electron-positron annihilation feature near the galactic center has been detected for more than half a century, yet its origin remains a mystery. In this paper, we describe a concept for a balloon-borne 511 keV $\gamma$-ray mission called the 511-Spectrometer Mission. The mission will use Transition-Edge Sensor (TES) arrays with thick metal absorbers that are thermally coupled to the TES. The strength of the approach is a projected energy resolution of 200 eV Full Width Half Maximum (FWHM) at 511 keV, enabling detailed studies of the shape and substructure of the 511 keV emission from the galactic center region. A first mission equipped with 8,192 $\gamma$-ray detectors and a fully active shield and collimator could detect the galactic center with ~35 $\sigma$ statistical significance. We present the mission concept as well as first results obtained with a prototype detector equipped with $1.35\times1.35\times2$ mm$^{3}$ Bi absorbers. The detector has a quantum efficiency of 15% for 511 keV photons in photoelectric effect interactions. In tests with a $^{137}$Cs source, these prototype detectors show an energy resolution of 525 eV FWHM at 662 keV. We end with a discussion of follow-up missions that use coded mask imaging, or use concentrating or focusing optics to scrutinize the sources of 511 keV $\gamma$-rays on smaller angular scales.

astro-ph.IM↗

arXiv2026

Seeking SOTA: Time-Series Forecasting Must Adopt Taxonomy-Specific Evaluation to Dispel Illusory Gains

We argue that the current practice of evaluating AI/ML time-series forecasting models, predominantly on benchmarks characterized by strong, persistent periodicities and seasonalities, obscures real progress by overlooking the performance of efficient classical methods. We demonstrate that these "standard" datasets often exhibit dominant autocorrelation patterns and seasonal cycles that can be effectively captured by simpler linear or statistical models, rendering complex deep learning architectures frequently no more performant than their classical counterparts for these specific data characteristics, and raising questions as to whether any marginal improvements justify the significant increase in computational overhead and model complexity. We call on the community to (I) retire or substantially augment current benchmarks with datasets exhibiting a wider spectrum of non-stationarities, such as structural breaks, time-varying volatility, and concept drift, and less predictable dynamics drawn from diverse real-world domains, and (II) require every deep learning submission to include robust classical and simple baselines, appropriately chosen for the specific characteristics of the downstream tasks' time series. By doing so, we will help ensure that reported gains reflect genuine scientific methodological advances rather than artifacts of benchmark selection favoring models adept at learning repetitive patterns.

cs.LG↗

arXiv2026

An Approximate Ascent Approach To Prove Convergence of PPO

Proximal Policy Optimization (PPO) is among the most widely used deep reinforcement learning algorithms, yet its theoretical foundations remain incomplete. Most importantly, convergence and understanding of fundamental PPO advantages remain widely open. Under standard theory assumptions we show how PPO's policy update scheme (performing multiple epochs of minibatch updates on multi-use rollouts with a surrogate gradient) can be interpreted as approximated policy gradient ascent. We show how to control the bias accumulated by the surrogate gradients and use techniques from random reshuffling to prove a convergence theorem for PPO that sheds light on PPO's success. Additionally, we identify a previously overlooked issue in truncated Generalized Advantage Estimation commonly used in PPO. The geometric weighting scheme induces infinite mass collapse onto the longest $k$-step advantage estimator at episode boundaries. Empirical evaluations show that a simple weight correction can yield substantial improvements in environments with strong terminal signal, such as Lunar Lander.

cs.LG↗

arXiv2025

Sub-nanosecond structural dynamics of the martensitic transformation in Ni-Mn-Ga

Martensitic transformations drive a multitude of emerging applications, which range from high stroke actuation and, mechanocaloric refrigeration, to thermoelastic energy harvesting. All these applications benefit from faster transformations, as a high cycle frequency is essential for achieving high power density. However, systematic investigations of the fast dynamics and fundamental speed limits of martensitic transformations are scarce. Especially for ultrashort time transformations, the temperature evolution throughout the transformation is not measured, which is a substantial shortcoming as temperature is the intrinsic force driving the transformation. Here, we present a synchrotron-based time-resolved X-ray diffraction study of a 270 fs laser-induced martensitic transformation in a Ni-Mn-Ga-based epitaxial thin film. We observe the transformation from martensite to austenite within about 100 ps, just limited by the synchrotron probe pulse duration. Furthermore, a full transformation cycle from martensite to austenite and back to martensite can almost be finished within 5 ns, which is the fastest martensitic transformation reported so far. Measurements and calculations of the temperature evolution allow us to analyse the influence of temperature on transformation time. By time-resolved strain measurements we demonstrate that in addition to temperature, thermal film stress must be considered as a competing influence on the martensitic transformation. Our experimental findings are supported by molecular dynamics simulations with machine learned force fields adapted to density functional theory calculations. These reveal that the huge distortion during a martensitic transformation requires the collective movement of many atoms within the microstructure, which delays the transformation.

cond-mat.mtrl-sci↗

arXiv2025

Demonstration of Advanced Timing Schemes in Time-Resolved X-ray Diffraction Measurements

We present time-resolved X-ray diffraction measurements using advanced timing schemes that provide high temporal resolution while also maintaining a high flux in the X-ray probe beam. The method employs patterned probe pulse sequences that are generated with the WaveGate solid-state pulse picker. We demonstrate the feasibility of our method at two different beamlines on millisecond and microsecond timescales.

cond-mat.mtrl-sci↗

arXiv2025

Towards Precision Spectroscopy of Antiprotonic Atoms for Probing Strong-field QED

PAX (antiProtonic Atom X-ray spectroscopy) is a new experiment with the aim to test strong-field quantum electrodynamics (QED) effects by performing high-precision x-ray spectroscopy of antiprotonic atoms. By utilizing advanced microcalorimeter detection techniques and a low-energy antiproton beam provided by the ELENA ring at CERN, gaseous targets will be used for the creation of antiprotonic atoms, and the measurement of transitions between circular Rydberg states will be conducted with up to two orders of magnitude improved accuracy over previous studies using high-purity germanium detectors. Our approach eliminates the longstanding issue of nuclear uncertainties that have hindered prior studies using highly charged ions, thus enabling direct and purely QED-focused measurements. By precisely probing atomic systems with electric fields up to two orders of magnitude above the Schwinger limit, PAX will test vacuum polarization and second-order QED corrections, opening new frontiers in fundamental physics and uncovering potential pathways to physics beyond the Standard Model.

physics.atom-ph↗

arXiv2024

Laser-initiated electron and heat transport in gold-skutterudite CoSb$_3$ bilayers resolved by pulsed x-ray scattering

Electron and lattice heat transport have been investigated in bilayer thin films of gold and CoSb$_3$ after photo-excitation of the nanometric top gold layer through picosecond x-ray scattering in a pump-probe setup. The unconventional observation of a larger portion of the deposited heat being detected first in the underlying CoSb$_3$ layer supports the picture of ballistic transport of the photo-excited electrons from gold to the underlying layer. The lattice expansion recorded by x-ray scattering allows accounting for the energy deposition and heat transport.

cond-mat.mtrl-sci↗

arXiv2023

Local and Global Trend Bayesian Exponential Smoothing Models

This paper describes a family of seasonal and non-seasonal time series models that can be viewed as generalisations of additive and multiplicative exponential smoothing models, to model series that grow faster than linear but slower than exponential. Their development is motivated by fast-growing, volatile time series. In particular, our models have a global trend that can smoothly change from additive to multiplicative, and is combined with a linear local trend. Seasonality when used is multiplicative in our models, and the error is always additive but is heteroscedastic and can grow through a parameter sigma. We leverage state-of-the-art Bayesian fitting techniques to accurately fit these models that are more complex and flexible than standard exponential smoothing models. When applied to the M3 competition data set, our models outperform the best algorithms in the competition as well as other benchmarks, thus achieving to the best of our knowledge the best results of per-series univariate methods on this dataset in the literature. An open-source software package of our method is available.

cs.LG↗

arXiv2023

Brain Model State Space Reconstruction Using an LSTM Neural Network

Objective Kalman filtering has previously been applied to track neural model states and parameters, particularly at the scale relevant to EEG. However, this approach lacks a reliable method to determine the initial filter conditions and assumes that the distribution of states remains Gaussian. This study presents an alternative, data-driven method to track the states and parameters of neural mass models (NMMs) from EEG recordings using deep learning techniques, specifically an LSTM neural network. Approach An LSTM filter was trained on simulated EEG data generated by a neural mass model using a wide range of parameters. With an appropriately customised loss function, the LSTM filter can learn the behaviour of NMMs. As a result, it can output the state vector and parameters of NMMs given observation data as the input. Main Results Test results using simulated data yielded correlations with R squared of around 0.99 and verified that the method is robust to noise and can be more accurate than a nonlinear Kalman filter when the initial conditions of the Kalman filter are not accurate. As an example of real-world application, the LSTM filter was also applied to real EEG data that included epileptic seizures, and revealed changes in connectivity strength parameters at the beginnings of seizures. Significance Tracking the state vector and parameters of mathematical brain models is of great importance in the area of brain modelling, monitoring, imaging and control. This approach has no need to specify the initial state vector and parameters, which is very difficult to do in practice because many of the variables being estimated cannot be measured directly in physiological experiments. This method may be applied using any neural mass model and, therefore, provides a general, novel, efficient approach to estimate brain model variables that are often difficult to measure.

cs.LG↗

arXiv2023

ASCENT - A balloon-borne hard X-ray imaging spectroscopy telescope using transition edge sensor microcalorimeter detectors

Core collapse supernovae are thought to be one of the main sources in the galaxy of elements heavier than iron. Understanding the origin of the elements is thus tightly linked to our understanding of the explosion mechanism of supernovae and supernova nucleosynthesis. X-ray and gamma-ray observations of young supernova remnants, combined with improved theoretical modeling, have resulted in enormous improvements in our knowledge of these events. The isotope ${}^{44}$Ti is one of the most sensitive probes of the innermost regions of the core collapse engine, and its spatial and velocity distribution are key observables. Hard X-ray imaging spectroscopy with the Nuclear Spectroscopic Telescope Array (NuSTAR) has provided new insights into the structure of the supernova remnant Cassiopeia A (Cas A), establishing the convective nature of the supernova engine. However, many questions about the details of this engine remain. We present here the concept for a balloon-borne follow-up mission called ASCENT (A SuperConducting ENergetic x-ray Telescope). ASCENT uses transition edge sensor gamma-ray microcalorimeter detectors with a demonstrated 55 eV Full Width Half Maximum (FWHM) energy resolution at 97 keV. This 8--16-fold improvement in energy resolution over NuSTAR will allow high resolution imaging and spectroscopy of the ${}^{44}$Ti emission. This will allow a detailed reconstruction of gamma-ray line redshifts, widths, and shapes, allowing us to address questions such as: What is the source of the neutron star "kicks"? What is the dominant production pathway for ${}^{44}$Ti? Is the engine of Cas A unique?

astro-ph.IM↗

arXiv2022

SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series Forecasting

Threshold Autoregressive (TAR) models have been widely used by statisticians for non-linear time series forecasting during the past few decades, due to their simplicity and mathematical properties. On the other hand, in the forecasting community, general-purpose tree-based regression algorithms (forests, gradient-boosting) have become popular recently due to their ease of use and accuracy. In this paper, we explore the close connections between TAR models and regression trees. These enable us to use the rich methodology from the literature on TAR models to define a hierarchical TAR model as a regression tree that trains globally across series, which we call SETAR-Tree. In contrast to the general-purpose tree-based models that do not primarily focus on forecasting, and calculate averages at the leaf nodes, we introduce a new forecasting-specific tree algorithm that trains global Pooled Regression (PR) models in the leaves allowing the models to learn cross-series information and also uses some time-series-specific splitting and stopping procedures. The depth of the tree is controlled by conducting a statistical linearity test commonly employed in TAR models, as well as measuring the error reduction percentage at each node split. Thus, the proposed tree model requires minimal external hyperparameter tuning and provides competitive results under its default configuration. We also use this tree algorithm to develop a forest where the forecasts provided by a collection of diverse SETAR-Trees are combined during the forecasting process. In our evaluation on eight publicly available datasets, the proposed tree and forest models are able to achieve significantly higher accuracy than a set of state-of-the-art tree-based algorithms and forecasting benchmarks across four evaluation metrics.

cs.LG↗

arXiv2022

The 511-CAM Mission: A Pointed 511 keV Gamma-Ray Telescope with a Focal Plane Detector Made of Stacked Transition Edge Sensor Microcalorimeter Arrays

The 511 keV gamma-ray emission from the galactic center region may fully or partially originate from the annihilation of positrons from dark matter particles with electrons from the interstellar medium. Alternatively, the positrons could be created by astrophysical sources, involving exclusively standard model physics. We describe here a new concept for a 511 keV mission called 511-CAM (511 keV gamma-ray CAmera using Micro-calorimeters) that combines focusing gamma-ray optics with a stack of Transition Edge Sensor (TES) microcalorimeter arrays in the focal plane. The 511-CAM detector assembly has a projected 511 keV energy resolution of 390 eV Full Width Half Maximum (FWHM) or better, and improves by a factor of at least 11 on the performance of state-of-the-art Ge-based Compton telescopes. Combining this unprecedented energy resolution with sub-arcmin angular resolutions afforded by Laue lens or channeling optics could make substantial contributions to identifying the origin of the 511 keV emission by discovering and characterizing point sources and measuring line-of-sight velocities of the emitting plasmas.

astro-ph.IM↗

arXiv2022

Measuring the electron neutrino mass using the electron capture decay of 163Ho

While the mass differences between neutrino mass states are known, their absolute masses and mass hierarchy have not yet been determined. Determining the mass of neutrinos provides access to physics beyond the Standard Model and the resulting value has implications for the growth of large-scale structure in the universe over cosmic history. Because of the importance of the topic, a number of efforts are already underway to determine the mass of neutrinos including direct kinematic measurements and indirect measurements of astrophysical phenomena that constrain the sum of the mass eigenstates through models of cosmic evolution. Here, we advocate for a collaborative international effort to perform a kinematic determination of the effective electron neutrino mass using calorimetric measurements of the decay of 163Ho. This effort is justified by the success of current experiments using the technique, its high benefit-to-cost ratio, the value of approaches with different systematic errors, and the value of measuring the electron neutrino mass rather than the electron anti-neutrino mass.

nucl-ex↗

arXiv2022

What is the speed limit of martensitic transformations?

Structural martensitic transformations enable various applications, which range from high stroke actuation and sensing to energy efficient magnetocaloric refrigeration and thermomagnetic energy harvesting. All these emerging applications benefit from a fast transformation, but up to now the speed limit of martensitic transformations has not been explored. Here, we demonstrate that a martensite to austenite transformation can be completed in under ten nanoseconds. We heat an epitaxial Ni-Mn-Ga film with a laser pulse and use synchrotron diffraction to probe the influence of initial sample temperature and overheating on transformation rate and ratio. We demonstrate that an increase of thermal energy drives this transformation faster. Though the observed speed limit of 2.5 x 10^{27} (Js)^{-1} per unit cell leaves plenty of room for a further acceleration of applications, our analysis reveals that the practical limit will be the energy required for switching. Our experiments unveil that martensitic transformations obey similar speed limits as in microelectronics, which are expressed by the Margolus-Levitin theorem.

cond-mat.mtrl-sci↗

arXiv2022

Quantification of 242Pu with a Microcalorimeter Gamma Spectrometer

We report measurements of the 103-keV and 159-keV gamma ray signatures of 242Pu using microcalorimetry. This is the first observation of these gamma rays in a non-destructive measurement of an unprepared sample, and so represents an important advance in nuclear material accountancy. The measurement campaign also serves as the first demonstration of a field campaign with a portable microcalorimeter gamma-ray spectrometer. For the 103-keV gamma ray we report an improved centroid energy and emission probability.

physics.ins-det↗

arXiv2022

Development of SiGe Indentation Process Control for Gate-All-Around FET Technology Enablement

Methodologies for characterization of the lateral indentation of silicon-germanium (SiGe) nanosheets using different non-destructive and in-line compatible metrology techniques are presented and discussed. Gate-all-around nanosheet device structures with a total of three sacrificial SiGe sheets were fabricated and different etch process conditions used to induce indent depth variations. Scatterometry with spectral interferometry and x-ray fluorescence in conjunction with advanced interpretation and machine learning algorithms were used to quantify the SiGe indentation. Solutions for two approaches, average indent (represented by a single parameter) as well as sheet-specific indent, are presented. Both scatterometry with spectral interferometry as well as x-ray fluorescence measurements are suitable techniques to quantify the average indent through a single parameter. Furthermore, machine learning algorithms enable a fast solution path by combining x-ray fluorescence difference data with scatterometry spectra, therefore avoiding the need for a full optical model solution. A similar machine learning model approach can be employed for sheet-specific indent monitoring; however, reference data from cross-section transmission electron microscopy image analyses are required for training. It was found that scatterometry with spectral interferometry spectra and a traditional optical model in combination with advanced algorithms can achieve a very good match to sheet-specific reference data.

physics.app-ph↗

arXiv2020

Formation dynamics of exciton polariton vortices created by non-resonant annular pumping

We study the spontaneous formation of exciton polariton vortices in an all-optical non-resonantly excited annular trap, which is formed by ring-shaped subpicosecond laser pulses. Since the light emitted by these vortices carries orbital angular momentum (OAM) corresponding to their topological charge, we apply a dedicated OAM spectroscopy technique to detect the OAM of the measurement signal with picosecond time resolution. This allows us to identify the formation of OAM modes and investigate the dynamics of the vortex formation process. We also study the power dependence of this process and how the ring diameter influences the formation of OAM modes.

physics.optics↗