Preprints

As quantum processors continue to scale in size and complexity, the need for well-defined, reproducible, and technology-agnostic performance metrics becomes increasingly critical. Here we present a suite of scalable quantum computing benchmarks developed as key performance indicators (KPIs) within the EU Quantum Flagship. [...]

Promoting brain health is vital for well-being and reducing healthcare burdens. Individual brain health asmeasured with the Brain Age Gap (BAG) - the difference between chronological and predicted brain age-relates to many factors. [...]

Electronic-structure theory is the foundation of the description of materials including multiscale modeling of their properties and functions. Obviously, without sufficient accuracy at the base, reliable predictions are unlikely at any level that follows. [...]

Recent advances in coherent conveyor-mode spin qubit shuttling are paving the way for large-scale quantum computing platforms with qubit connectivity achieved by spin qubit shuttles. We developed a simulation tool to investigate numerically the impact of device imperfections on the spin-coherence of conveyor-mode shuttling in Si/SiGe. [...]

The prospect of achieving fault-tolerant quantum computing with semiconductor spin qubits in Si/SiGe heterostructures relies on the integration of a large number of identical devices, a feat achievable through a scalable (Bi)CMOS manufacturing approach. To this end, both the gate stack and the Si/SiGe heterostructure must be of high quality, exhibiting uniformity across the wafer and consistent performance across multiple fabrication runs. [...]

For self-triggered readout of SiPM sum signals, a waveform classification can aid a simple threshold trigger to reliably extract calorimetric particle hit information online at an early stage and thus reduce the volume of transmitted data. Typically, the ADC data acquisition is based on FPGAs for edge data processing. [...]

Memristors are promising devices for scalable and low power, in-memory computing to improve the energy efficiency of a rising computational demand. The crossbar array architecture with memristors is used for vector matrix multiplication (VMM) and acts as kernels in neuromorphic computing. [...]