The tomographic reconstruction of the state of a quantum-mechanical system is an essential component in the development of quantum technologies. We present an overview of different tomographic methods for determining the quantum-mechanical density matrix of a single qubit: (scaled) direct inversion, maximum likelihood estimation (MLE), minimum Fisher information distance and Bayesian mean estimation (BME). We discuss the different prior densities in the space of density matrices, on which both MLE and BME depend, as well as ways of including experimental errors and of estimating tomography errors. As a measure of the accuracy of these methods, we average the trace distance between a given density matrix and the tomographic density matrices ...
We describe in detail the theory underpinning the measurement of density matrices of a pair of quant...
One of the fundamental problems of experimental quantum physics is the determination of the state of...
Given an experimental setup and a fixed number of measurements, how should one take data to optimall...
The tomographic reconstruction of the state of a quantum-mechanical system is an essential component...
Quantum state tomography is the task of inferring the state of a quantum system by appropriate measu...
Quantum state tomography is the task of inferring the state of a quantum system by appropriate measu...
Quantum state tomography (QST) is essential for characterizing unknown quantum states. Several metho...
Quantum state tomography (QST) is a technique used to reconstruct the density matrix of unknown quan...
We describe quantum tomography as an inverse statistical problem in which the quantum state of a lig...
We describe quantum tomography as an inverse statistical problem in which the quantum state of a lig...
We describe quantum tomography as an inverse statistical problem in which the quantum state of a lig...
We describe quantum tomography as an inverse statistical problem in which the quantum state of a lig...
We describe quantum tomography as an inverse statistical problem in which the quantum state of a lig...
Summary. The quantum state of a light beam can be represented as an infinite dimensional density mat...
Summary. | "Quantum Tomography " is a general method for estimating arbitrary ensemble ave...
We describe in detail the theory underpinning the measurement of density matrices of a pair of quant...
One of the fundamental problems of experimental quantum physics is the determination of the state of...
Given an experimental setup and a fixed number of measurements, how should one take data to optimall...
The tomographic reconstruction of the state of a quantum-mechanical system is an essential component...
Quantum state tomography is the task of inferring the state of a quantum system by appropriate measu...
Quantum state tomography is the task of inferring the state of a quantum system by appropriate measu...
Quantum state tomography (QST) is essential for characterizing unknown quantum states. Several metho...
Quantum state tomography (QST) is a technique used to reconstruct the density matrix of unknown quan...
We describe quantum tomography as an inverse statistical problem in which the quantum state of a lig...
We describe quantum tomography as an inverse statistical problem in which the quantum state of a lig...
We describe quantum tomography as an inverse statistical problem in which the quantum state of a lig...
We describe quantum tomography as an inverse statistical problem in which the quantum state of a lig...
We describe quantum tomography as an inverse statistical problem in which the quantum state of a lig...
Summary. The quantum state of a light beam can be represented as an infinite dimensional density mat...
Summary. | "Quantum Tomography " is a general method for estimating arbitrary ensemble ave...
We describe in detail the theory underpinning the measurement of density matrices of a pair of quant...
One of the fundamental problems of experimental quantum physics is the determination of the state of...
Given an experimental setup and a fixed number of measurements, how should one take data to optimall...