Maximal entropy approach for quantum state tomography
arXiv:2009.00815 · doi:10.1103/PRXQuantum.2.010318
Abstract
Quantum computation has been growing rapidly in both theory and experiments. In particular, quantum computing devices with a large number of qubits have been developed by IBM, Google, IonQ, and others. The current quantum computing devices are noisy intermediate-scale quantum NISQ devices, and so approaches to validate quantum processing on these quantum devices are needed. One of the most common ways of validation for an n-qubit quantum system is quantum tomography, which tries to reconstruct a quantum system's density matrix by a complete set of observables. However, the inherent noise in the quantum systems and the intrinsic limitations poses a critical challenge to precisely know the actual measurement operators which make quantum tomography impractical in experiments. Here, we propose an alternative approach to quantum tomography, based on the maximal information entropy, that can predict the values of unknown observables based on the available mean measurement data. This can then be used to reconstruct the density matrix with high fidelity even though the results for some observables are missing. Of additional contexts, a practical approach to the inference of the quantum mechanical state using only partial information is also needed.
27 pages, 6 figures, submitted to PRX Quantum
References in corpus (18)
- Quantum Computing in the NISQ era and beyond
- Hardware-efficient Variational Quantum Eigensolver for Small Molecules and Quantum Magnets
- On the Measurement of Qubits
- Quantum state tomography via compressed sensing
- Review of Decoherence Free Subspaces, Noiseless Subsystems, and Dynamical Decoupling
- Detector Tomography on IBM 5-qubit Quantum Computers and Mitigation of Imperfect Measurement
- Self-guided quantum tomography
- Quantum State and Process Tomography of Energy Transfer Systems via Ultrafast Spectroscopy
- Quantum process tomography of molecular dimers from two-dimensional electronic spectroscopy I: General theory and application to homodimers
- Quantum-classical hybrid algorithm using an error-mitigating -representability condition to compute the Mott metal-insulator transition
- Quantum tomography as a tool for the characterization of optical devices
- Quantum computing methods for electronic states of the water molecule
- Quantum State Tomography with incomplete data: Maximum Entropy and Variational Quantum Tomography
- Reconstruction of quantum states of spin systems via the Jaynes principle of maximum entropy
- Quantum Process Tomography by 2D Fluorescence Spectroscopy
- Quantum State Reconstruction From Incomplete Data
- The IBM Quantum Computer and the IBM Quantum Experience
- Determination of the full statistics of quantum observables using the maximum entropy method
Cited by in corpus (9)
- Quantum Machine Learning for Chemistry and Physics
- Convergence of reconstructed density matrix to a pure state using maximal entropy approach
- Variational Approach to Quantum State Tomography based on Maximal Entropy Formalism
- Quantum Gram-Schmidt Processes and Their Application to Efficient State Read-out for Quantum Algorithms
- Simulating noisy quantum channels via quantum state preparation algorithms
- Hamiltonian learning from time dynamics using variational algorithms
- Dimension reduction and redundancy removal through successive Schmidt decompositions
- Principle of Information Increase: An Operational Perspective of Information Gain in the Foundations of Quantum Theory
- Random Projection using Random Quantum Circuits