plaquette-ftqc-hardware-design

name	plaquette-ftqc-hardware-design
description	Hardware-aware design platform for fault-tolerant quantum computers (FTQCs). Computes logical performance from device physics using Kraus operators, Hamiltonian-Lindblad dynamics, and quantum channels across four sampler classes.
tags	["quantum","fault-tolerance","hardware-aware","error-mitigation","statistics"]
created	2026-07-10
source	arxiv
arxiv_id	2607.08767

Overview

Plaquette is a theoretical framework and software suite that computes the logical performance of fault-tolerant quantum architectures directly from the physics of hardware imperfections. Bridges the gap between open-system device physics and FTQC logical performance.

Key Problem

Hardware noise departs from stochastic Pauli models:

• Superconducting transmons: leak out of computational subspace
• Neutral atoms: scatter through intermediate states
• Trapped ions: heat via motion mode phonon absorption
• Miscalibrated controls: over-rotate coherently

Four Sampler Classes

1. Stabilizer Sampling

• For Pauli noise models
• Standard approach, scalable
• May fall short for non-Pauli errors

2. XPauli Sampler (NEW)

• Handles leakage and environment sectors
• Near-Clifford accuracy for non-Pauli errors
• Matches full-state simulation within statistical uncertainty

3. Near-Clifford Samplers

• For coherent errors (over-rotations, crosstalk)
• Bridges gap between Clifford-only and full simulation

4. Full-State Simulation

• Exact reference calculations
• Limited to small systems
• Used for validation

Workflow

1. Specify Error Model: Kraus operators, Hamiltonian-Lindblad dynamics, or experimentally reconstructed quantum channel
2. Compile to Samplers: Automatically compile into representations required by each sampler class
3. Validate: Compare XPauli/near-Clifford against full-state simulation
4. Compute Logical Performance: Get FTQC thresholds, error budgets, overhead estimates

Platform-Specific Error Models

Superconducting Qubits

• Leakage errors (|2⟩ state population)
• XPauli sampler captures leakage dynamics

Neutral Atoms

• Intermediate-state scattering during gates
• Environment sector modeling

Trapped Ions

• Motional mode heating (phonon absorption)
• Requires full Lindblad treatment for accuracy

Core Findings

• Pauli twirling can fall short depending on error model
• Discrepancy size varies with platform and noise process
• Reliable thresholds require most accurate simulation available
• Direct path from open-system physics to FTQC logical performance

Pitfalls

Pauli Twirling Limitations

• Does not capture leakage or coherent errors accurately
• Can underestimate error rates significantly
• Use XPauli or near-Clifford samplers when noise is non-Pauli

Sampler Selection

• XPauli: best for leakage and environment sectors
• Near-Clifford: best for coherent errors
• Full-state: only for small-system validation
• Stabilizer: only for purely Pauli noise

Statistical Uncertainty

• XPauli matches full-state within statistical uncertainty
• Ensure sufficient sampling for reliable estimates
• Monitor convergence of logical error rate estimates

Implementation

# Conceptual workflow:
# 1. Define error model as Kraus operators or Lindbladian
# 2. Plaquette compiles to appropriate sampler representations
# 3. Run FTQC simulation with selected sampler
# 4. Extract logical error rates, thresholds, overheads
# 5. Compare across sampler classes for validation

References

• arXiv:2607.08767 "Plaquette: A hardware-aware design platform for fault-tolerant quantum computers"
• Authors: Conchello Vendrell et al.