Javascript must be enabled to continue!
Bosonic Quantum Computational Complexity
View through CrossRef
Quantum computing involving physical systems with continuous degrees of freedom, such as the quantum states of light, has recently attracted significant interest. However, a well-defined quantum complexity theory for these bosonic computations over infinite-dimensional Hilbert spaces is missing. In this work, we lay foundations for such a research program. We introduce natural complexity classes and problems based on bosonic generalizations of BQP, the local Hamiltonian problem, and QMA. We uncover several relationships and subtle differences between standard Boolean classical and discrete variable quantum complexity classes and identify outstanding open problems. In particular:
1. We show that the power of quadratic (Gaussian) quantum dynamics is equivalent to the class BQL. More generally, we define classes of continuous-variable quantum polynomial time computations with a bounded probability of error based on higher-degree gates. Due to the infinite dimensional Hilbert space, it is not a priori clear whether a decidable upper bound can be obtained for these classes. We identify complete problems for these classes and demonstrate a BQP lower and EXPSPACE upper bound. We further show that the problem of computing expectation values of polynomial bosonic observables is in PSPACE.
2. We prove that the problem of deciding the boundedness of the spectrum of a bosonic Hamiltonian is co-NP-hard. Furthermore, we show that the problem of finding the minimum energy of a bosonic Hamiltonian critically depends on the non-Gaussian stellar rank of the family of energy-constrained states one optimizes over: for constant stellar rank, it is NP-complete; for polynomially-bounded rank, it is in QMA; for unbounded rank, it is undecidable.
Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften
Title: Bosonic Quantum Computational Complexity
Description:
Quantum computing involving physical systems with continuous degrees of freedom, such as the quantum states of light, has recently attracted significant interest.
However, a well-defined quantum complexity theory for these bosonic computations over infinite-dimensional Hilbert spaces is missing.
In this work, we lay foundations for such a research program.
We introduce natural complexity classes and problems based on bosonic generalizations of BQP, the local Hamiltonian problem, and QMA.
We uncover several relationships and subtle differences between standard Boolean classical and discrete variable quantum complexity classes and identify outstanding open problems.
In particular:
1.
We show that the power of quadratic (Gaussian) quantum dynamics is equivalent to the class BQL.
More generally, we define classes of continuous-variable quantum polynomial time computations with a bounded probability of error based on higher-degree gates.
Due to the infinite dimensional Hilbert space, it is not a priori clear whether a decidable upper bound can be obtained for these classes.
We identify complete problems for these classes and demonstrate a BQP lower and EXPSPACE upper bound.
We further show that the problem of computing expectation values of polynomial bosonic observables is in PSPACE.
2.
We prove that the problem of deciding the boundedness of the spectrum of a bosonic Hamiltonian is co-NP-hard.
Furthermore, we show that the problem of finding the minimum energy of a bosonic Hamiltonian critically depends on the non-Gaussian stellar rank of the family of energy-constrained states one optimizes over: for constant stellar rank, it is NP-complete; for polynomially-bounded rank, it is in QMA; for unbounded rank, it is undecidable.
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...
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 Computing and Quantum Information Science
Quantum Computing and Quantum Information Science
Abstract:
Quantum Computing and Quantum Information Science offers a comprehensive, interdisciplinary exploration of the mathematical principles, computational models, and engineer...
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...
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...
Quantum-Enhanced Artificial Intelligence: Framework for Hybrid Computing and Natural Language Processing
Quantum-Enhanced Artificial Intelligence: Framework for Hybrid Computing and Natural Language Processing
The convergence of quantum computing and artificial intelligence represents a paradigm shift in computational capability, enabling solutions to previously intractable optimization ...
Quantum Cryptographic Primitives
Quantum Cryptographic Primitives
The main motivation of this thesis is the uncertain panorama of cybersecurity risks and threats, accentuated by the arrival of the quantum computer. This type of computer is comple...

