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Updated: May 16, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

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Published on: September 8, 2023

Solving Constrained Optimization Problems Using Hybrid Qubit-Qumode Quantum Devices.

Rishab Dutta1, Brandon Allen1, Chuzhi Xu1

  • 1Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States.

Journal of Chemical Theory and Computation
|May 14, 2026
PubMed
Summary
This summary is machine-generated.

Hybrid qubit-qumode quantum devices efficiently solve optimization problems using the Echoed Conditional Displacement Variational Quantum Eigensolver (ECD-VQE). This method outperforms existing algorithms, offering better solutions with fewer resources for complex computational tasks.

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Last Updated: May 16, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

  • Quantum Computing
  • Quantum Information Science
  • Computational Optimization

Background:

  • Variational Quantum Algorithms (VQAs) are a key approach for near-term quantum hardware.
  • Quadratic Unconstrained Binary Optimization (QUBO) problems are prevalent in various scientific and industrial domains.
  • Hybrid qubit-qumode systems offer a novel platform for quantum computation.

Purpose of the Study:

  • To demonstrate the efficacy of hybrid qubit-qumode devices for solving QUBO problems.
  • To introduce and apply the Echoed Conditional Displacement Variational Quantum Eigensolver (ECD-VQE) for optimization.
  • To compare ECD-VQE performance against existing quantum algorithms like QAOA.

Main Methods:

  • Utilizing circuit quantum electrodynamics (cQED) architectures for hybrid qubit-qumode implementation.
  • Encoding QUBO instances across multiple qumodes coupled to a single qubit.
  • Extracting binary solutions via photon-number measurements.
  • Applying the ECD-VQE algorithm to the Binary Knapsack Problem.

Main Results:

  • ECD-VQE on hybrid qubit-qumode devices achieved higher-quality solutions than QAOA on conventional qubit circuits.
  • The ECD-VQE approach required significantly fewer resources compared to QAOA.
  • Demonstrated applicability of ECD-VQE to chemistry problems, specifically active-space selection.
  • Showcased shallower circuit depths for state preparation using variational ECD ansatz.

Conclusions:

  • Hybrid qubit-qumode platforms are efficient for solving NP-hard and chemistry-related optimization problems.
  • ECD-VQE on qubit-qumode systems offers a promising advantage over qubit-only architectures.
  • Qubit-qumode gates are strong candidates for constrained optimization in early fault-tolerant quantum computing.