Guido Menichetti

We present a study of the energy resolution of transition-edge sensors (TESs) for the detection of electrons in the 100-eV kinetic energy range. The TES is a Ti-Au bilayer with an active area of ( 60 × 60 ) μ m 2 and a critical temperature of approximately 80 mK . The electron source is based on vertically aligned multiwall carbon nanotubes located inside the cryostat, with electrons generated via field emission. For electrons in the ( 92 – 99 ) eV kinetic energy range, we obtain a Gaussian energy resolution for fully absorbed electrons of ( 0.48 ± 0.04 ± 0.06 ) eV , where the first uncertainty is statistical and the second systematic. When considering the full-width at half-maximum of the peak of the signal amplitude distribution, the corresponding resolution is of ( 1.4 ± 0.2 ± 0.3 ) eV . The former represents an improvement of ( 47 – 60 ) % with respect to previous results and is mainly attributed to the reduction in the TES active area. The latter is instead an improvement of over a factor of 21 and is mainly due to the reduction in the emitting area of the electron source, which significantly suppresses electron back-scattering in proximity of the TES. These results represent a major milestone toward high-precision spectroscopy on low-energy electrons, which is a key objective for the PTOLEMY experiment.

We present the results of a multimethodological study aimed at investigating the interaction between graphene and tritium during its β -decay to helium, under different levels of loading and geometrical configurations. We combine density-functional theory (DFT) to evaluate the interaction potentials, with calculations of the decay rate, in order to study the consequences that the presence of the substrate has on the β -decay spectrum of tritium. We determine the shape of the event rate, accounting for the effects of (part of) the corresponding condensed-matter degrees of freedom. In the context of future neutrino experiments, our results provide important information aimed at the optimization of hosting material. Furthermore, our work outlines a novel theoretical and computational scheme to account for the different timescales involved in the process and to address a question at the boundary between high- and low-energy physics. This requires nonconventional declinations of DFT combined with full quantum treatments of the nuclear configuration involved in the decay process. Our results pave the way for future studies aimed at determining the physics reach of upcoming neutrino mass experiments.

Spin-wave excitations are fundamental to understanding the behavior of magnetic materials and hold promise for future information and communication technologies. Yet, modeling these accurately in transition-metal compounds remains challenging, starting from the self-interaction errors affecting localized and partially filled d orbitals in density-functional theory (DFT) with (semi)local functionals. In this work, we compare three advanced first-principles approaches for computing magnetic exchange parameters and magnon dispersions in NiO and MnO, all based on a common DFT + U ground state with Hubbard U values obtained from density-functional perturbation theory. Two methods extract exchange parameters directly: one via total-energy differences using the four-state mapping ( Δ E ), and the other via the magnetic force theorem (MFT) using infinitesimal spin rotations. Magnon dispersions are then obtained from a Heisenberg Hamiltonian through linear spin-wave theory (LSWT). The third approach, time-dependent density-functional perturbation theory with U ( TDDFPT + U ), yields magnon dispersions directly from the dynamical spin susceptibility, with exchange parameters fitted , for comparison, via LSWT. Our results show that TDDFPT + U and the Heisenberg model based on Δ E -derived parameters align well with experimental neutron scattering data, whereas the MFT-based approach shows larger discrepancies, possibly due to some inherent approximations and limitations of the particular implementation used. This study benchmarks the accuracy of state-of-the-art first-principles techniques for spin-wave modeling and contributes to advancing reliable computational tools for the study and design of magnetic materials.