Abstract Machine learning algorithms are powerful tools for data-driven tasks such as image
classification and feature detection. However, their vulnerability to adversarial examples …

In the past decade, the toolkit of quantum information has been expanded to include
processes in which the basic operations do not have definite causal relations. Originally …

The field of classical stochastic processes forms a major branch of mathematics. Stochastic
processes are, of course, also very well studied in biology, chemistry, ecology, geology …

Characterization protocols have so far played a central role in the development of noisy
intermediate-scale quantum (NISQ) computers capable of impressive quantum feats. This …

While several numerical techniques are available for predicting the dynamics of non-
Markovian open quantum systems, most struggle with simulations for very long memory and …

The impressive pace of advance of quantum technology calls for robust and scalable
techniques for the characterization and validation of quantum hardware. Quantum process …

Excitement about the promise of quantum computers is tempered by the reality that the
hardware remains exceptionally fragile and error prone, forming a bottleneck in the …

The prevalence of quantum crosstalk in current quantum devices poses challenges for
achieving high-fidelity quantum logic operations and reliable quantum processing. Through …

Non-Markovian noise presents a particularly relevant challenge in understanding and
combating decoherence in quantum computers, yet is challenging to capture in terms of …

Improving the speed and fidelity of quantum logic gates is essential to reach quantum
advantage with future quantum computers. However, fast logic gates lead to increased …