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A survey on the complexity of learning quantum states
Quantum learning theory is a new and very active area of research at the intersection of
quantum computing and machine learning. Important breakthroughs in the past two years …
quantum computing and machine learning. Important breakthroughs in the past two years …
Random unitaries in extremely low depth
We prove that random quantum circuits on any geometry, including a 1D line, can form
approximate unitary designs over $ n $ qubits in $\log n $ depth. In a similar manner, we …
approximate unitary designs over $ n $ qubits in $\log n $ depth. In a similar manner, we …
On the role of entanglement and statistics in learning
In this work we make progress in understanding the relationship between learning models
when given access to entangled measurements, separable measurements and statistical …
when given access to entangled measurements, separable measurements and statistical …
Quantum Information Processing, Sensing, and Communications: Their Myths, Realities, and Futures
The recent advances in quantum information processing, sensing, and communications are
surveyed with the objective of identifying the associated knowledge gaps and formulating a …
surveyed with the objective of identifying the associated knowledge gaps and formulating a …
Learning unitaries with quantum statistical queries
We propose several algorithms for learning unitary operators from quantum statistical
queries (QSQs) with respect to their Choi-Jamiolkowski state. Quantum statistical queries …
queries (QSQs) with respect to their Choi-Jamiolkowski state. Quantum statistical queries …
Learning quantum processes with quantum statistical queries
Learning complex quantum processes is a central challenge in many areas of quantum
computing and quantum machine learning, with applications in quantum benchmarking …
computing and quantum machine learning, with applications in quantum benchmarking …
Quantum local differential privacy and quantum statistical query model
Quantum statistical queries provide a theoretical framework for investigating the
computational power of a learner with limited quantum resources. This model is particularly …
computational power of a learner with limited quantum resources. This model is particularly …
Local random quantum circuits form approximate designs on arbitrary architectures
We consider random quantum circuits (RQC) on arbitrary connected graphs whose edges
determine the allowed $2 $-qudit interactions. Prior work has established that such $ n …
determine the allowed $2 $-qudit interactions. Prior work has established that such $ n …
Latent Style-based Quantum GAN for high-quality Image Generation
Quantum generative modeling is among the promising candidates for achieving a practical
advantage in data analysis. Nevertheless, one key challenge is to generate large-size …
advantage in data analysis. Nevertheless, one key challenge is to generate large-size …
Agnostic process tomography
Characterizing a quantum system by learning its state or evolution is a fundamental problem
in quantum physics and learning theory with a myriad of applications. Recently, as a new …
in quantum physics and learning theory with a myriad of applications. Recently, as a new …