# Full Quantum state tomography with Linear Inversion

Jump to: navigation, search

Quantum state tomography is the process by which a quantum state is reconstructed using a series of measurements in different basis on an ensemble of identical quantum states. Because measurement of a quantum state typically changes the state being measured, getting a complete picture of that state requires measurements on many state copies. The method described here perform quantum state tomography using linear inversion.

## Assumptions

• Noise is assumed to be independent and identically distributed.
• The selected measurement basis should be tomographically complete.

## Outline

Quantum state tomography attempts to characterize an unknown state ρ by measuring its components, usually in the Pauli basis or a different selected basis of measurement operators. Multiple identical copies of the quantum state are required as different measurements need to be performed on each copy. To fully reconstruct the density matrix for a mixed state, this method is used. This procedure can be used to completely characterize an unknown apparatus.

This method consists of the following steps:

• An unknown state is prepared multiple times so as to create many copies.
• The experimenter picks a basis of measurement operators.
• The measurement corresponding to each measurement operator in the selected basis is taken multiple times. This is used to approximate the probability of measuring the state in the value corresponding to the measurement operator.
• With the knowledge of the probabilities and the chosen measurement basis, the density matrix of the quantum state is calculated using matrix inversion.

## Hardware Requirements

• Trusted Measurement device.

## Notation

• ${\displaystyle d}$: Dimension of Hilbert space
• ${\displaystyle \rho }$: Density matrix of the prepared quantum state
• ${\displaystyle E_{j}}$: Different measurement operators of a selected basis, where ${\displaystyle j=1,...,d^{2}}$
• ${\displaystyle A}$: Select basis of measurement with the different measurement operators ${\displaystyle E_{j}}$
• ${\displaystyle p_{j}}$: Probability of the state corresponding to ${\displaystyle E_{j}}$
• ${\displaystyle N}$: Number of single shots corresponding to a measurement operator. This is used to calculate probability
• ${\displaystyle m_{j}}$: Sample average of ${\displaystyle N}$ single shot measurements of ${\displaystyle E_{j}}$.
• ${\displaystyle m_{ij}}$: Outcome of the ${\displaystyle i^{th}}$ measurement from ${\displaystyle N}$ single shot measurements. ${\displaystyle m_{ij}\in \{0,1\}}$
• ${\displaystyle E(m_{j})}$: Expected value of ${\displaystyle m_{j}}$
• ${\displaystyle E(m_{ij})}$: Expected value of ${\displaystyle m_{ij}}$

## Properties

• The figure of merit: Density Matrix of the quantum state
• Multiple copies of the quantum state are required in this method.
• The measurement basis ${\displaystyle E_{j}}$ should be chosen such that ${\displaystyle A_{jk}}$ is invertible to calculate the density matrix. Hence, ${\displaystyle E_{j}}$ should be tomographically complete.
• This method is extremely resource-intensive.
• The main drawback of this technique is that sometimes the computed solution of the density matrix will not be a valid density matrix. This issue occurs when not enough measurements are made. Due to this drawback, the maximum likelihood estimation technique is preferred over this linear inversion technique.
• Another drawback of this method is that an infinite number of measurement outcomes would be required to give the exact solution.
• State preparation and measurement errors are taken into consideration in this method. The measurement errors are tackled by increasing the accuracy of the measuring apparatus.
• Error from counting statistics can also occur which are reduced by performing the measurements on a larger ensemble.
• Drift error can occur either in the state produced or the efficiency of the detection system and it can constrain data collection time.
• In addition to the mentioned errors, each experimental implementation can have its own unique errors.

## Procedure Description

Input: copies of unknown quantum state

Output: Density matrix of the quantum state, ${\displaystyle \rho }$

• Pick the measurement basis ${\displaystyle A}$, where ${\displaystyle A={\begin{bmatrix}{\vec {E_{1}}}\\{\vec {E_{2}}}\\.\\.\\{\vec {E_{d^{2}}}}\end{bmatrix}}}$
• For ${\displaystyle j=1,2,...,d^{2}}$:
• For ${\displaystyle i=1,2,...,N}$:
• Measure ${\displaystyle \rho }$ with measurement operator ${\displaystyle E_{j}}$
• Get measurement result ${\displaystyle m_{ij}}$
• Calculate ${\displaystyle m_{j}=\sum _{i=1}^{N}m_{ij}/N}$
• Estimate ${\displaystyle p_{j},p_{j}=E(m_{j})=\sum _{i=1}^{N}E_{(}m_{ij})/N}$
• Define ${\displaystyle {\vec {p}}}$, where ${\displaystyle {\vec {p}}={\begin{bmatrix}p_{1}\\p_{2}\\.\\.\\p_{d^{2}}\end{bmatrix}}}$
• Form relation ${\displaystyle A{\vec {\rho }}={\begin{bmatrix}{\vec {E_{1}}}{\vec {\rho }}\\{\vec {E_{2}}}{\vec {\rho }}\\.\\.\\{\vec {E_{d^{2}}}}{\vec {\rho }}\end{bmatrix}}={\begin{bmatrix}E_{1}\cdot \rho \\E_{2}\cdot \rho \\.\\.\\E_{d^{2}}\cdot \rho \end{bmatrix}}={\begin{bmatrix}P(E_{1}|\rho )\\P(E_{2}|\rho )\\.\\.\\P(E_{d^{2}}|\rho )\end{bmatrix}}={\begin{bmatrix}p_{1}\\p_{2}\\.\\.\\p_{d^{2}}\end{bmatrix}}={\vec {p}}}$
• Use matrix inversion to get ${\displaystyle \rho }$, where ${\displaystyle {\vec {\rho }}=(A^{T}A)^{-1}A^{T}{\vec {p}}}$

## Further Information

• Maximum likelihood estimation(also known as MLE or MaxLik) is a popular technique for dealing with the problems of linear inversion.
• Bayesian mean estimation (BME) is another approach which addresses the problems of maximum likelihood estimation
• Homodyne tomography focuses on the electromagnetic field, where the tomographic observables are obtained from homodyne detection.

## Related Papers

• J. B. Altepeter et al, Quantum State Tomography
• Z Hradil Physical Review A, 55(3):1561–1564, 1997: Quantum-state estimation.
• D. Leibfried et al Phys. Rev. Lett. 77, 4281 (1996)
• J. Rehacek et al arXiv:quant-ph/0009093: Iterative algorithm for reconstruction of entangled states
• Robin Blume-Kohout arXiv:quant-ph/0611080v1: Optimal, reliable estimation of quantum states
• G. M. D'Ariano et al arXiv:quant-ph/0507078: Homodyne tomography and the reconstruction of quantum states of light
*contributed by Rhea Parekh