Related papers: Extensive Comparison between INRIM and a Secondary…
The latest results of benchmarking research are presented for a variety of beyond-CMOS charge- and spin-based devices. In addition to improving the device-level models, several new device proposals and a few majorly modified devices are…
This work presents a scalable method to produce robust all-solid electric double layer capacitors (EDLCs), compatible with roll-to-roll processes and structural laminate composite fabrication. It consists in sandwiching and pressing an…
The Electron-Ion Collider provides a groundbreaking opportunity to study heavy pentaquarks with unprecedented precision, leveraging its high collision energy and beam spin polarization capabilities. As a representative case, we analyze…
X-ray polarimetry promises to give qualitatively new information about high-energy astrophysical sources, such as binary black hole systems, micro-quasars, active galactic nuclei, neutron stars, and gamma-ray bursts. We designed, built and…
Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks in various domains. Despite their impressive performance, they can be unreliable due to factual errors in their generations. Assessing their…
Large language models (LLMs) often produce unsupported or unverifiable content, known as "hallucinations." To mitigate this, retrieval-augmented LLMs incorporate citations, grounding the content in verifiable sources. Despite such…
Accurate X-ray spectroscopic measurements are fundamental for deriving basic physical parameters of the most abundant baryon components in the Universe. The plethora of X-ray observatories currently operational enables a panchromatic view…
Uncertainty estimates must be calibrated (i.e., accurate) and sharp (i.e., informative) in order to be useful. This has motivated a variety of methods for recalibration, which use held-out data to turn an uncalibrated model into a…
The Inert Doublet Model (IDM) is a simple extension of the Standard Model, introducing an additional Higgs doublet that brings in four new scalar particles. The lightest of the IDM scalars is stable and is a good candidate for a dark matter…
Aided inertial navigation system (INS), typically consisting of an inertial measurement unit (IMU) and an exteroceptive sensor, has been widely accepted as a feasible solution for navigation. Compared with vision-aided and LiDAR-aided INS,…
Various properties of the general two-center two-electron integral over the explicitly correlated exponential function are analyzed for the potential use in high precision calculations for diatomic molecules. A compact one dimensional…
At National Institute of Metrological Research (INRIM), a selectable-value Transportable High dcVoltage Standard (THVS) operating in the range from 10 V to 100 V in steps of 10 V, was developed. This Standard was built to cover the lack of…
Indirect comparisons have been increasingly used to compare data from different sources such as clinical trials and observational data in, e.g., a disease registry. To adjust for population differences between data sources,…
In this paper, an Extreme Learning Machine (ELM) based technique for Multi-label classification problems is proposed and discussed. In multi-label classification, each of the input data samples belongs to one or more than one class labels.…
There is a need for techniques for efficient and accurate measurement of the impedance of rechargeable batteries at extra-low frequencies (ELFs, typically below 10uHz), as these reflect real usage and cycling patterns, and their importance…
In this lecture, the physics potential for the e+e- linear collider experiments ILC and CLIC is reviewed. The experimental conditions are compared to those at hadron colliders and their intrinsic value for precision experiments,…
Excalibur is a non-parametric, hierarchical framework for precision wavelength-calibration of spectrographs. It is designed with the needs of extreme-precision radial velocity (EPRV) in mind, which require that instruments be calibrated or…
Proper confidence calibration of deep neural networks is essential for reliable predictions in safety-critical tasks. Miscalibration can lead to model over-confidence and/or under-confidence; i.e., the model's confidence in its prediction…
Recent research in retrieval-augmented generation (RAG) has concentrated on retrieving useful information from candidate documents. However, numerous methodologies frequently neglect the calibration capabilities of large language models…
This paper describes an analysis performed at 250 GeV centre of mass energy for the reaction e+e- -> bbbar with the International Linear Collider, ILC, assuming an integrated luminosity of 500 fb-1. This measurement requires determining the…