Positron annihilation lifetime spectroscopy (PALS) spectra are commonly analyzed by fitting multi-exponential lifetime models convoluted with the detector resolution function. In practice, this inverse problem is sensitive to initial parameter choices, parameter bounds, source corrections, and correlations between lifetime and intensity parameters. This paper presents fitPALSpectra, an open-source Python workflow for configurable PALS spectrum simulation, fitting, visualization, and reporting. The implementation uses an analytically integrated exponential--Gaussian response model, configurable source and sample components, constrained optimization, optional least-squares refinement, and machine-readable output of fit results, correlation matrices, and fitted curves. Validation on fully synthetic spectra with known ground-truth parameters shows accurate recovery of the simulated lifetimes, intensities, detector full width at half maximum, prompt shift, and background.

This Letter presents a novel analytical framework showing that the dark count probability (PDC) of perimeter-gated single-photon avalanche diodes (pg-SPADs) follows a complementary Gompertz function. Specifically, we show that PDC follows a complementary Gompertz form from which we derive a pixel-specific descriptor, the midpoint perimeter gate voltage, which characterizes a pixel's equiprobable operating point. We further show that a perimeter gate voltage compensation rate may be obtained from this descriptor to offset temperature-induced changes in the pixel's activation function. The proposed framework is experimentally validated using 4,096 pg-SPADs arranged in a 64 x 64 array and manufactured in a 0.35 $\mu$m CMOS process. The devices were characterized at temperatures ranging from -5 $^o$C to 55 $^o$C and perimeter gate voltage magnitudes of 0 to 5 V. The measured results demonstrate deterministic bias control of dark count probability across process and temperature variations.

We introduce SPADE (SPlit And Delay Embeddings), an autoregressive transformer for sequences whose tokens carry multiple features. Rather than embedding these features jointly, SPADE embeds them independently. Delaying each feature stream relative to the previous one allows intra-token correlations to be learned by the standard self-attention mechanism. Applied to point-cloud calorimeter shower generation in the highly granular ILD detector, SPADE is competitive with the state of the art AllShowers model on photon showers, and substantially outperforms its VQ-VAE-based predecessor OmniJet-$\alpha_C$. The mechanism is applicable to any generative task with multi-feature tokens, enabling LLM-style pretraining workflows for higher-dimensional data.

The present research applies Graph Neural-Networks (GNNs) for energy measurement and particle identification tasks for a proposed second detector at the future Electron Ion Collider (EIC). In particular, an iron-scintillator sampling calorimeter would provide neutral hadron ($K_L$ and neutron) energy measurements and identification, as well as separation of muons from hadrons. Using detector simulations, particle hits in the detector are represented as graphs, and a GNN is trained for either classification or prediction. Furthermore, we developed a parameterization of the scintillator optical photon simulation that yields a 20-fold speed up compared to the default simulation. We find that the GNN method outperforms classical methods at the same tasks, and we report projections for the energy and timing resolution, and identification accuracy of the calorimeter. We also present an integration of the GNN method into a Multi-Objective Optimization framework, enabled by an automated pipeline of data generation, GNN training, and detector performance evaluation. We utilize the optimization to quantify the tradeoffs between different performance metrics at high and low energies when changing the detector design parameters, such as the iron/scintillator thickness.

Optical Fabry-Perot cavities are crucial tools for metrology experiments, where they achieve extreme length stability, and for some atomic physics experiments, where tunability to atomic transitions enables atom-light interactions. However, achieving both frequency stability and tunability in a single cavity has remained a challenge, forcing metrology experiments exploiting atom-cavity interactions to rely on external active feedback systems to stabilize the length of the cavity. Here, we describe a piezoelectrically-tunable cavity with a cancellation of the coefficient of thermal expansion at around $5^\circ\mathrm{C}$, achieving fractional frequency instabilities at the $4\times 10^{-13}$ level for 1~s integration time. This advance eliminates the need for external stabilization in many atom-cavity experiments, making this design ideal for applications such as ultra-stable superradiant lasers and other cavity quantum electrodynamics experiments.

In the search for axionic Dark Matter, the high frequency part of the QCD axion parameter space is favored, as indicated by both cosmological and astrophysical arguments and recent indications from lattice QCD calculations. To extend the probing range of cavity haloscopes, solutions addressing the unfavorable scaling of cavity volume with frequency must be developed. Here, we present a novel type of high-volume thin shell resonator for high frequency haloscope dark matter searches. The cavity is formed by two nested and coaxial right angle polygonal prisms enclosed within two flat endcaps. For the axion-sensitive (pseudo-)TM010 mode, finite element simulations yield form factor of the order of 0.8 and Q factor of the order of 60000 for a copper cavity at 4$\,$K. High tunability of up to $\sim 5\%$ is achieved by reciprocal rotation of the two prisms, without significant changes in haloscope sensitivity. A prototype aluminium hexagonal cavity was built and tested, confirming the main characteristics of the design.

A traveling wave parametric amplifier has been integrated in the haloscope of the QUAX experiment. A search for dark matter axions has been performed with a high Q dielectric cavity immersed in a 8 T magnetic field and read by a detection chain having a system noise temperature of about 2.1 K at the frequency of 10.353 GHz. Scanning has been conducted by varying the cavity frequency using sapphire rods immersed into the cavity. At multiple operating frequencies, the sensitivity of the instrument was at the level of viable axion models.