Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Full-stack Physics-level model of cascaded entanglement links

J. Gabriel Richardson, Prajit Dhara, Abhishek Bhatt, Saikat Guha, Stefan Krastanov

TL;DR

The paper tackles the challenge of achieving high-rate, high-fidelity entanglement distribution for quantum networks and proposes the ZALM cascaded source as a practical solution. It develops a comprehensive full-stack modeling framework that blends Gaussian and non-Gaussian formalisms, using covariance matrices, the K-function to density-matrix mapping, Wick's theorem, and Hafnian-based methods, implemented in the open-source genqo toolkit and integrated with QuantumSymbolics.jl and QuantumSavory.jl. A key finding is that increasing the mean photon number Ns can offset transmission and detection losses to boost the generation probability P_gen, enabling potential distillation-based rate enhancements at the expense of some fidelity. The work delivers a reproducible software ecosystem and demonstrates how high-fidelity, multiplexed entanglement can be analyzed and engineered within a complete network simulator, advancing the practical deployment of ZALM-based quantum networks.

Abstract

While the last few decades have seen a proliferation of experimental demonstrations of entanglement sources, practicality of deployment has been a secondary concern. Recently, the ZALM source was introduced, as a well engineered functional device, easily integrated within a complete networking system. It addresses numerous concerns which make typical academic demonstrations less practical: reliable heralding signals, multiplexing across multiple dimensions, and efficient use of input power. We present a stack of tools for modeling mode by mode a ZALM source under realistic conditions, in isolation, or as a part of a complete network testbed. Our modeling formalism builds upon a hybrid Gaussian and non-Gaussian representation, providing a flexible tradeoff between performance and accuracy, while also greatly simplifying the exact calculation of otherwise expensive scalar figures of merit. This toolkit, implemented in the python package called genqo, is integrated within the QuantumSavory full stack simulator and the QuantumSymbolics computer algebra system. We use this software stack to demonstrate a number of complete networking protocols built upon the ZALM source.

Full-stack Physics-level model of cascaded entanglement links

TL;DR

The paper tackles the challenge of achieving high-rate, high-fidelity entanglement distribution for quantum networks and proposes the ZALM cascaded source as a practical solution. It develops a comprehensive full-stack modeling framework that blends Gaussian and non-Gaussian formalisms, using covariance matrices, the K-function to density-matrix mapping, Wick's theorem, and Hafnian-based methods, implemented in the open-source genqo toolkit and integrated with QuantumSymbolics.jl and QuantumSavory.jl. A key finding is that increasing the mean photon number Ns can offset transmission and detection losses to boost the generation probability P_gen, enabling potential distillation-based rate enhancements at the expense of some fidelity. The work delivers a reproducible software ecosystem and demonstrates how high-fidelity, multiplexed entanglement can be analyzed and engineered within a complete network simulator, advancing the practical deployment of ZALM-based quantum networks.

Abstract

While the last few decades have seen a proliferation of experimental demonstrations of entanglement sources, practicality of deployment has been a secondary concern. Recently, the ZALM source was introduced, as a well engineered functional device, easily integrated within a complete networking system. It addresses numerous concerns which make typical academic demonstrations less practical: reliable heralding signals, multiplexing across multiple dimensions, and efficient use of input power. We present a stack of tools for modeling mode by mode a ZALM source under realistic conditions, in isolation, or as a part of a complete network testbed. Our modeling formalism builds upon a hybrid Gaussian and non-Gaussian representation, providing a flexible tradeoff between performance and accuracy, while also greatly simplifying the exact calculation of otherwise expensive scalar figures of merit. This toolkit, implemented in the python package called genqo, is integrated within the QuantumSavory full stack simulator and the QuantumSymbolics computer algebra system. We use this software stack to demonstrate a number of complete networking protocols built upon the ZALM source.
Paper Structure (39 sections, 107 equations, 2 figures)

This paper contains 39 sections, 107 equations, 2 figures.

Table of Contents

  1. Introduction
  2. Physical Principles
  3. The Heralding Process
  4. Using Quantum Memories
  5. Definition of Performance Metrics
  6. Physical Modeling Parameters
  7. Mathematical Principles
  8. Gaussian Model via Covariance Matrices
  9. Covariance Matrix of the Two Mode Squeezed Vacuum State
  10. Covariance Matrix of a Dual-Rail Entanglement source
  11. Initial Covariance Matrix of the Cascaded/ZALM Source
  12. Bell State Measurement
  13. From Gaussian to Density Matrix
  14. $K$-Function Formalism
  15. Incorporating Loss
  16. ...and 24 more sections

Figures (2)

  • Figure 1: A diagram showing the construction of both the SPDC source and the cascaded/ZALM source in terms of operations on optical modes. TMSV refers to two-mode squeezed vacuum state, SPDC refers to the SPDC source mentioned in the text. We give arbitrary indices to the modes, for referencing in the main text, however we do not impose any specific physical implementation of the source. The heralding mechanism achieved by the cascaded source via an entanglement swap between half of the modes from two SPDC sources is essential for ZALM operation. This is because it enables frequency multiplexing without introducing a large quantum memory overhead, as would be required for frequency multiplexing unheralded SPDC source. Cascading also enables source operation in a higher mean photon number regime as compared to the SPDC source, since the heralding mechanism essentially filters undesirable higher-photon-order terms.
  • Figure 2: The probability of successful heralded pair generation versus the mean photon number, calculated using both our hybrid Gaussian/non-Gaussian model (black/green/blue) as well as the older low-mean-photon-number-approximation (red). An important property uncovered by our more precise model is that the peak generation probability does not plummet with increased loss -- one simply needs a high mean photon number to compensate. Naturally, the fidelity of entanglement will drop at higher mean photon numbers due to multi-photon events, nonetheless this discovery opens up exciting future prospects in employing distillation to achieve unexpectedly high rates of generation at good fidelities.