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We study the fundamental efficiency of delimited control. Specifically, we show that effect handlers enable an asymptotic improvement in runtime complexity for a certain class of functions. We consider the generic count problem using a pure PCF-like base language $lambda_b$ and its extension with effect handlers $lambda_h$. We show that $lambda_h$ admits an asymptotically more efficient implementation of generic count than any $lambda_b$ implementation. We also show that this efficiency gap remains when $lambda_b$ is extended with mutable state. To our knowledge this result is the first of its kind for control operators.
Context-Oriented Programming (COP) is a programming paradigm to encourage modularization of context-dependent software. Key features of COP are layers---modules to describe context-dependent behavioral variations of a software system---and their dyna
Weak-head normalization is inconsistent with functional extensionality in the call-by-name $lambda$-calculus. We explore this problem from a new angle via the conflict between extensionality and effects. Leveraging ideas from work on the $lambda$-cal
With quantum computers of significant size now on the horizon, we should understand how to best exploit their initially limited abilities. To this end, we aim to identify a practical problem that is beyond the reach of current classical computers, bu
We investigate the qubit in the hierarchical environment where the first level is just one lossy cavity while the second level is the N-coupled lossy cavities. In the weak coupling regime between the qubit and the first level environment, the dynamic
Asynchronous and parallel implementation of standard reinforcement learning (RL) algorithms is a key enabler of the tremendous success of modern RL. Among many asynchronous RL algorithms, arguably the most popular and effective one is the asynchronou