What Is A QST Quantum State Tomography? How Does It Works
Quantum State Tomography (QST) is vital for identifying a system's unknown quantum state by measuring several identical clones. Since measuring a quantum particle changes or destroys its state, it is difficult to take several measurements on the same quantum system, unlike classical items that may be tested again. Thus, QST needs data from an ensemble of identically prepared quantum states to reconstruct a complete image.
Describe Quantum State Tomography.
QST aims to identify a quantum state's density matrix mathematical description. The density matrix captures all quantitative quantum system attributes in a “mixed state” (a statistical mixing of pure states) or “pure state” (all particles in the ensemble are identical). CT scans use multiple two-dimensional projections, or “slices,” to build a three-dimensional image.
QST also uses several “projections” or measurements to understand a quantum state. Tomographic estimates of the Wigner distribution were proposed in the late 1980s.
How QST Works
The Measurement Process
In the QST process, the same quantum state is prepared again and measured in various bases using “tomographic” or “projective” methods. Each measurement provides unique status information. Quantum State Tomography (QST) requires measurements in at least three bases for a single qubit (a two-level quantum system, such as photon polarisation). These measurements, often presented on a Poincaré or Bloch sphere, are used to derive state parameters. A single qubit's over-complete set usually has six projective measurements.
Besides polarisation, spatial modes carrying orbital angular momentum (OAM) can encode qubits, and spatial light modulators can describe their states on an OAM Bloch sphere. With more qubits, complexity increases rapidly. QST in multi-particle systems requires contemporaneous projective measurements on every particle. Characterising a two-qubit system requires 36 projective measurements. Tensor products of single-ququbit Pauli matrices and eigenstates are used in these investigations.
Reconstructing Density Matrix
The density matrix must be recreated when measurement data is collected. The “object” (the quantum state) is deduced from its “shadows” (the measurement results) in reverse.
Linear Inversion: Born's formula and observed probability solve a system of linear equations directly in the simplest method, linear inversion. A major downside is its capacity to construct non-physical density matrices with negative probability. Maximum Likelihood Estimation (MLE): This popular method avoids linear inversion by searching for the density matrix in the physically valid space (Hermitian, unit trace, non-negative eigenvalues) that best fits the experimental data. MLE can sometimes produce zero eigenvalues with 100% certainty after finite measurements, which may not always be warranted. Bayesian methods use previous information and “honest” estimations with error ranges to ensure that the reconstructed state is within physical limitations.
Issues and Limitations
The biggest challenge for Quantum State Tomography (QST) is system scalability. More qubits require more measurements and computational resources. Systems with more than a few qubits cannot achieve full QST due to the “curse of dimensionality”.
Experimental noise affects measurement results and must be considered. To solve these issues, researchers have developed tomography methods that need fewer measurements or simpler post-processing. Post-processing and local measurements are often used with matrix product states (MPS) for systems with specific correlation structures. Compressed sensing and permutationally invariant quantum tomography reduce measurement costs by assuming state qualities like low rank or symmetry.
Classical Implementations: Instructor and Research Tool Bright classical light can reproduce and show QST, making it useful for research and education without the issues of single photons.
Based on Klyshko's “time reversal” concept, backprojection with scalar light uses a powerful laser source instead of a quantum detector. Although classical light tracks backward, it faithfully replicates quantum experiments, including entire QSTs. This aids quantum experiment coordination and prediction.
Quantum State Tomography (QST) using Classically Entangled Light (Vector Beams) uses mathematical similarities between classical and quantum states. Spatially variable polarisation vector beams are “classically entangled” because their spatial and polarisation degrees of freedom are not separable. QST tests can imitate numerous characteristics of quantum entanglement using conventional optical components. Despite accurately representing many quantum events, these classical systems cannot replace quantum experiments for applications like quantum key distribution, which depend on inherent quantum properties.
DIY Lab Implementation and Uses
DIY lab solutions like 3D-printed electromechanical roto-flip stages for automating polarisation optics make QST more accessible. Research and education benefit from faster and more reliable studies.
QST is crucial to modern quantum technologies. This tool is used to debug quantum circuits, characterise entanglement sources, validate quantum algorithms, and compare quantum devices. Concurrence, linear entropy, and reconstructed density matrix fidelity quantify state quality, purity, and entanglement.
Quantum State Tomography (QST) helps debug and verify quantum information technology by describing quantum states completely. However, exponential scalability for bigger systems remains a fundamental challenge, motivating research on more reliable and effective tomography methods.
