Stochastic fluctuations of molecule numbers are ubiquitous in biological systems. Important
examples include gene expression and enzymatic processes in living cells. Such systems …

The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical
variational algorithm designed to tackle combinatorial optimization problems. Despite its …

The combinatorial problem of learning directed acyclic graphs (DAGs) from data was
recently framed as a purely continuous optimization problem by leveraging a differentiable …

Strongly driven systems of emitters offer an attractive source of light over broad spectral
ranges up to the X-ray region. A key limitation of these systems is that the light they emit is …

In this review, we give a comprehensive comparison of the most widely used coherent state
(CS) based methods to solve the time-dependent Schrödinger equation (TDSE). Starting …

The heat kernel is a type of graph diffusion that, like the much-used personalized PageRank
diffusion, is useful in identifying a community nearby a starting seed node. We present the …

The implicit trace estimation problem asks for an approximation of the trace of a square
matrix, accessed via matrix-vector products (matvecs). This paper designs new randomized …

The high level of control and precision achievable in current synthetic quantum matter
setups has enabled first attempts at quantum-simulating various intriguing phenomena in …

Fine-scale rates of meiotic recombination vary by orders of magnitude across the genome
and differ between species and even populations. Studying cross-population differences …

We introduce Neural Marching Cubes, a data-driven approach for extracting a triangle mesh
from a discretized implicit field. We base our meshing approach on Marching Cubes (MC) …