Quantum tomography of entangled qubits by time-resolved single-photon counting with time-continuous measurements
arXiv:2103.14085 · doi:10.1007/s11128-022-03682-8
Abstract
In this article, we introduce a framework for entanglement characterization by time-resolved single-photon counting with measurement operators defined in the time domain. For a quantum system with unitary dynamics, we generate time-continuous measurements by shifting from the Schrodinger picture to the Heisenberg representation. In particular, we discuss this approach in reference to photonic tomography. To make the measurement scheme realistic, we impose timing uncertainty on photon counts along with the Poisson noise. Then, the framework is tested numerically on quantum tomography of qubits. Next, we investigate the accuracy of the model for polarization-entangled photon pairs. Entanglement detection and precision of state reconstruction are quantified by figures of merit and presented on graphs versus the amount of time uncertainty.
References in corpus (6)
- Experimental Quantum State Tomography of Optical Fields and Ultrafast Statistical Sampling
- Quantum state tomography by continuous measurement and compressed sensing
- Relations between entanglement, Bell-inequality violation and teleportation fidelity for the two-qubit X states
- Implementation of quantum state tomography for time-bin qudits
- Phase estimation of time-bin qudits by time-resolved single-photon counting
- Quantum Tomography of Pure States with Projective Measurements Distorted by Experimental Noise
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- Effects of Chromatic Dispersion on Single-Photon Temporal Wave Functions in Quantum Communications
- Optimizing QKD efficiency by addressing chromatic dispersion and time measurement uncertainty
- Optimizing Continuous-Wave-Pumped Entanglement-based QKD in Noisy Environments