Computational nanotechnology articles from across Nature Portfolio

Probabilistic inference hardware prevents overconfidence. Lee et al. report a Gaussian-like memory transistor using p-n junction coupled with separate floating gate, offering precise control of the Gaussian outputs, simplified circuit design, and low power consumption for inference computing.

Improving signal to noise ratio of Raman spectra is vital for the application. Here, authors show a noise learning method that learns the noise feature of a spectrometer. This improves the signal to noise ratio and makes deep learning to be instrument dependent instead of sample dependent.

Combinatorial optimization problems can be solved on parallel hardware called Ising machines. Most studies have focused on the use of second-order Ising machines. Compared to second-order Ising machines, the authors show that higher-order Ising machines realized with coupled-oscillator networks can be more resource-efficient and provide superior solutions for constraint satisfaction problems.

Three-dimensional computing systems made of vertically integrated complementary metal–oxide–semiconductor circuits and layered resistive memory can perform analogue computing-in-memory with high energy efficiency.