Javascript must be enabled to continue!
An operational definition of quantum information scrambling
View through CrossRef
Abstract
Quantum information scrambling (QIS) is a characteristic feature of several quantum systems, ranging from black holes to quantum communication networks. While accurately quantifying QIS is crucial to understanding many such phenomena, common approaches based on the tripartite information have limitations due to the accessibility issues of quantum mutual information, and do not always properly take into consideration the dependence on the encoding input basis. To address these issues, we propose a novel and computationally efficient QIS quantifier, based on a formulation of QIS in terms of quantum state discrimination. We show that the optimal guessing probability, which reflects the degree of QIS induced by an isometric quantum evolution, is directly connected to the accessible min-information, a generalized channel capacity based on conditional min-entropy, which can be cast as a convex program and thus computed efficiently. By applying our proposal to a range of examples with increasing complexity, we illustrate its ability to capture the multifaceted nature of QIS in all its intricacy.
Title: An operational definition of quantum information scrambling
Description:
Abstract
Quantum information scrambling (QIS) is a characteristic feature of several quantum systems, ranging from black holes to quantum communication networks.
While accurately quantifying QIS is crucial to understanding many such phenomena, common approaches based on the tripartite information have limitations due to the accessibility issues of quantum mutual information, and do not always properly take into consideration the dependence on the encoding input basis.
To address these issues, we propose a novel and computationally efficient QIS quantifier, based on a formulation of QIS in terms of quantum state discrimination.
We show that the optimal guessing probability, which reflects the degree of QIS induced by an isometric quantum evolution, is directly connected to the accessible min-information, a generalized channel capacity based on conditional min-entropy, which can be cast as a convex program and thus computed efficiently.
By applying our proposal to a range of examples with increasing complexity, we illustrate its ability to capture the multifaceted nature of QIS in all its intricacy.
Related Results
Advanced frameworks for fraud detection leveraging quantum machine learning and data science in fintech ecosystems
Advanced frameworks for fraud detection leveraging quantum machine learning and data science in fintech ecosystems
The rapid expansion of the fintech sector has brought with it an increasing demand for robust and sophisticated fraud detection systems capable of managing large volumes of financi...
Advancements in Quantum Computing and Information Science
Advancements in Quantum Computing and Information Science
Abstract: The chapter "Advancements in Quantum Computing and Information Science" explores the fundamental principles, historical development, and modern applications of quantum co...
Integrating quantum neural networks with machine learning algorithms for optimizing healthcare diagnostics and treatment outcomes
Integrating quantum neural networks with machine learning algorithms for optimizing healthcare diagnostics and treatment outcomes
The rapid advancements in artificial intelligence (AI) and quantum computing have catalyzed an unprecedented shift in the methodologies utilized for healthcare diagnostics and trea...
Quantum information outside quantum information
Quantum information outside quantum information
Quantum theory, as counter-intuitive as a theory can get, has turned out to make predictions of the physical world that match observations so precisely that it has been described a...
Revolutionizing multimodal healthcare diagnosis, treatment pathways, and prognostic analytics through quantum neural networks
Revolutionizing multimodal healthcare diagnosis, treatment pathways, and prognostic analytics through quantum neural networks
The advent of quantum computing has introduced significant potential to revolutionize healthcare through quantum neural networks (QNNs), offering unprecedented capabilities in proc...
Information-Geometric Limits on Quantum Simulations of Black Hole Scrambling
Information-Geometric Limits on Quantum Simulations of Black Hole Scrambling
Strongly chaotic quantum systems, including black holes, exhibit rapid scrambling of initially local information, posing fundamental challenges for their faithful simulation in fin...
Entanglement and Geometrical Distances in Quantum Information and Quantum Cryptography
Entanglement and Geometrical Distances in Quantum Information and Quantum Cryptography
The counter-intuitive features of Quantum Mechanics make it possible to solve problems and perform tasks that are beyond the abilities of classical computers and classical communic...
Quantum metamaterials: Applications in quantum information science
Quantum metamaterials: Applications in quantum information science
Metamaterials are a class of artificially engineered materials with periodic structures possessing exceptional properties not found in conventional materials. This definition can b...

