Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Springer eBooks

Queuing Theory Models for (Fault-Tolerant) Quantum Circuits: Analysis and Optimization

Robert Basmadjian, Alexandru Paler

Published Aug 7, 2023• 1 citation
Publisher
DOI
10.1007/978-3-031-37966-6_8

Related papers

Microscopic quantum dynamics study on the noise threshold of fault-tolerant quantum error correction

Yuan‐Chung Cheng, R. Silbey

Quantum circuits implementing fault-tolerant quantum error correction (QEC) for the three-qubit bit-flip code and five-qubit code are studied. To describe the effect of noise, we apply a model based on a generalized effective Hamiltonian where the system-environment interactions are taken into account by including stochastic fluctuating terms in the system Hamiltonian. This noise model enables us to investigate the effect of noise in quantum circuits under realistic device conditions and avoid strong assumptions such as maximal parallelism and weak storage errors. Noise thresholds of the QEC codes are calculated. In addition, the effects of imprecision in projective measurements, collective bath, fault-tolerant repetition protocols, and level of parallelism in circuit constructions on the threshold values are also studied with emphasis on determining the optimal design for the fault-tolerant QEC circuit. These results provide insights into the fault-tolerant QEC process as well as useful information for designing the optimal fault-tolerant QEC circuit for particular physical implementation of quantum computer.

arXiv:quant-ph/0412168•Physical Review A•Jul 19, 2005•11 citations

Quantum fault-tolerant circuits

Hafiz Md. Hasan Babu

Institute of Physics eBooks•May 1, 2020•0 citations

Comparative Analysis of Fault-Tolerant Implementation of Quantum Logic

Mamtha Prajapati, Kalyan Babu Killana

The need to consider fault-tolerant quantum circuits is essential due to the intrinsic fragility of quantum systems. Recent studies have focused on optimizing complexity, resource utilization, and error resilience to enhance execution efficiency on quantum hardware. This paper performs a comparative analysis of fault-tolerant implementation approaches for quantum circuit design, emphasizing resource optimization, scalability, and error resilience. This paper illustrates recent designs that include enhanced Toffoli gate decompositions with reduced T-depths and resource-effective designs, demonstrating the tradeoffs among T-depth, T-gate count, and ancilla usage. These insights facilitate developing effective, scalable, and reliable quantum computing solutions, which are essential for both near-term quantum computation and future advancements.

International Conference on Device Intelligence, Computing and Communication Technologies (DICCT)•Mar 21, 2025•5 citations

A Fully Fault-Tolerant Representation of Quantum Circuits

Alexandru Paler, Ilia Polian, Kae Nemoto +1 more

arXiv:1509.03962•Lecture notes in computer science•Jan 1, 2015•15 citations

Modeling quantum circuits

Margareta Vamos

•Jan 1, 2011•1 citation

A Review of Variational Quantum Algorithms: Insights into Fault-Tolerant Quantum Computing

Zhirao Wang, Junxiang Huang, Runyu Ye +8 more

Variational quantum algorithms (VQAs) have established themselves as a central computational paradigm in the Noisy Intermediate-Scale Quantum (NISQ) era. By coupling parameterized quantum circuits (PQCs) with classical optimization, they operate effectively under strict hardware limitations. However, as quantum architectures transition toward early fault-tolerant (EFT) and ultimate fault-tolerant (FT) regimes, the foundational principles and long-term viability of VQAs require systematic reassessment. This review offers an insightful analysis of VQAs and their progression toward the fault-tolerant regime. We deconstruct the core algorithmic framework by examining ansatz design and classical optimization strategies, including cost function formulation, gradient computation, and optimizer selection. Concurrently, we evaluate critical training bottlenecks, notably barren plateaus (BPs), alongside established mitigation strategies. The discussion then explores the EFT phase, detailing how the integration of quantum error mitigation and partial error correction can sustain algorithmic performance. Addressing the FT phase, we analyze the inherent challenges confronting current hybrid VQA models. Furthermore, we synthesize recent VQA applications across diverse domains, including many-body physics, quantum chemistry, machine learning, and mathematical optimization. Ultimately, this review outlines a theoretical roadmap for adapting quantum algorithms to future hardware generations, elucidating how variational principles can be systematically refined to maintain their relevance and efficiency within an error-corrected computational environment.

quant-pharXiv:2604.07909•Apr 10, 2026•0 citations
Quantum circuits implementing fault-tolerant quantum error correction (QEC) for the three-qubit bit-flip code and five-qubit code are studied. To describe the effect of noise, we apply a model based on a generalized effective Hamiltonian where the system-environment interactions are taken into account by including stochastic fluctuating terms in the system Hamiltonian. This noise model enables us to investigate the effect of noise in quantum circuits under realistic device conditions and avoid strong assumptions such as maximal parallelism and weak storage errors. Noise thresholds of the QEC codes are calculated. In addition, the effects of imprecision in projective measurements, collective bath, fault-tolerant repetition protocols, and level of parallelism in circuit constructions on the threshold values are also studied with emphasis on determining the optimal design for the fault-tolerant QEC circuit. These results provide insights into the fault-tolerant QEC process as well as useful information for designing the optimal fault-tolerant QEC circuit for particular physical implementation of quantum computer.
The need to consider fault-tolerant quantum circuits is essential due to the intrinsic fragility of quantum systems. Recent studies have focused on optimizing complexity, resource utilization, and error resilience to enhance execution efficiency on quantum hardware. This paper performs a comparative analysis of fault-tolerant implementation approaches for quantum circuit design, emphasizing resource optimization, scalability, and error resilience. This paper illustrates recent designs that include enhanced Toffoli gate decompositions with reduced T-depths and resource-effective designs, demonstrating the tradeoffs among T-depth, T-gate count, and ancilla usage. These insights facilitate developing effective, scalable, and reliable quantum computing solutions, which are essential for both near-term quantum computation and future advancements.
Variational quantum algorithms (VQAs) have established themselves as a central computational paradigm in the Noisy Intermediate-Scale Quantum (NISQ) era. By coupling parameterized quantum circuits (PQCs) with classical optimization, they operate effectively under strict hardware limitations. However, as quantum architectures transition toward early fault-tolerant (EFT) and ultimate fault-tolerant (FT) regimes, the foundational principles and long-term viability of VQAs require systematic reassessment. This review offers an insightful analysis of VQAs and their progression toward the fault-tolerant regime. We deconstruct the core algorithmic framework by examining ansatz design and classical optimization strategies, including cost function formulation, gradient computation, and optimizer selection. Concurrently, we evaluate critical training bottlenecks, notably barren plateaus (BPs), alongside established mitigation strategies. The discussion then explores the EFT phase, detailing how the integration of quantum error mitigation and partial error correction can sustain algorithmic performance. Addressing the FT phase, we analyze the inherent challenges confronting current hybrid VQA models. Furthermore, we synthesize recent VQA applications across diverse domains, including many-body physics, quantum chemistry, machine learning, and mathematical optimization. Ultimately, this review outlines a theoretical roadmap for adapting quantum algorithms to future hardware generations, elucidating how variational principles can be systematically refined to maintain their relevance and efficiency within an error-corrected computational environment.