217 citations · 1.3k across the 53 of their papers we have counts for
8 papers · 1 filter
Magic of Random Matrix Product States
Liyuan Chen, Roy J. Garcia, Kaifeng Bu +1
Magic, or nonstabilizerness, characterizes how far away a state is from the stabilizer states, making it an important resource in quantum computing, under the formalism of the Gott…
Wasserstein Complexity of Quantum Circuits
Lu Li, Kaifeng Bu, Dax Enshan Koh +2
Given a unitary transformation, what is the size of the smallest quantum circuit that implements it? This quantity, known as the quantum circuit complexity, is a fundamental proper…
Resource theory of quantum scrambling
Roy J. Garcia, Kaifeng Bu, Arthur Jaffe
Quantum scrambling refers to the spread of local quantum information into the many degrees of freedom of a quantum system. In this work, we introduce a resource theory of scramblin…
Barren plateaus from learning scramblers with local cost functions
Roy J. Garcia, Chen Zhao, Kaifeng Bu +1
The existence of barren plateaus has recently revealed new training challenges in quantum machine learning (QML). Uncovering the mechanisms behind barren plateaus is essential in u…
Privacy-Utility Trade-Off
Hao Zhong, Kaifeng Bu
In this paper, we investigate the privacy-utility trade-off (PUT) problem, which considers the minimal privacy loss at a fixed expense of utility. Several different kinds of privac…
Complexity of quantum circuits via sensitivity, magic, and coherence
Kaifeng Bu, Roy J. Garcia, Arthur Jaffe +2
Quantum circuit complexity-a measure of the minimum number of gates needed to implement a given unitary transformation-is a fundamental concept in quantum computation, with widespr…
Classical shadows with Pauli-invariant unitary ensembles
Kaifeng Bu, Dax Enshan Koh, Roy J. Garcia +1
The classical shadow estimation protocol is a noise-resilient and sample-efficient quantum algorithm for learning the properties of quantum systems. Its performance depends on the…
Quantifying scrambling in quantum neural networks
Roy J. Garcia, Kaifeng Bu, Arthur Jaffe
We characterize a quantum neural network's error in terms of the network's scrambling properties via the out-of-time-ordered correlator. A network can be trained by optimizing eith…