Quantum Random Lunch Generator (QRLG)
Lunch is important and choosing where to have lunch is difficult. In this paper we demonstrate use of quantum randomness to find a place to eat, thus shifting the decision-making to the vacuum fluctuations of the universe. This QRLG is made publicly available.
Code (1)
Tasks
Decision MakingSimilar Papers 제목 키워드 기반
Noise-tolerant learnability of shallow quantum circuits from statistics and the cost of quantum pseudorandomness
In this work, we study the learnability of quantum circuits in the near term. We demonstrate the natural robustness of quantum statistical queries for learning quantum processes, motivating their use as a theoretical too…
Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets
The no-free-lunch (NFL) theorem is a celebrated result in learning theory that limits one's ability to learn a function with a training data set. With the recent rise of quantum machine learning, it is natural to ask whe…
BIG-bench Machine LearningLearning TheoryQuantum Machine LearningQonFusion -- Quantum Approaches to Gaussian Random Variables: Applications in Stable Diffusion and Brownian Motion
In the present study, we delineate a strategy focused on non-parametric quantum circuits for the generation of Gaussian random variables (GRVs). This quantum-centric approach serves as a substitute for conventional pseud…
Virtual Quantum Markov Chains
Quantum Markov chains generalize classical Markov chains for random variables to the quantum realm and exhibit unique inherent properties, making them an important feature in quantum information theory. In this work, we …
Separable Power of Classical and Quantum Learning Protocols Through the Lens of No-Free-Lunch Theorem
The No-Free-Lunch (NFL) theorem, which quantifies problem- and data-independent generalization errors regardless of the optimization process, provides a foundational framework for comprehending diverse learning protocols…
AttributeQuantum Machine Learning