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Problem Comparison

All quantum problems with real Azure Quantum Resource Estimator data. Click column headers to sort.

Physical Qubits by Problem

Problem ▲AlgorithmStagePhysical Qubits Logical Qubits T-Gates Rotations Runtime
Catalysis SimulationQPEStage C131.9k186453.3ms
Climate ModelingHHLStage C130.2k183352.3ms
Database SearchGroverStage C119.6k1800208.8μs
Drug DiscoveryQPEStage C130.2k186312.3ms
Error CorrectionQECStage C1.8k18008.4μs
FactorizationShorStage C77.3k2563215.6μs
High-Frequency TradingAmplitude Est.Stage C60.7k120157.6μs
Hubbard ModelQPEStage C131.9k186453.3ms
Linear SolversHHLStage C139.9k1812372.3ms
Materials DiscoveryQPEStage C131.9k186453.3ms
Nuclear PhysicsQPEStage C131.9k186453.3ms
PhotovoltaicsQuantum WalkStage C138.4k12010888.8μs
Post-Quantum CryptographyGroverStage C32.5k120036.4μs
Protein FoldingQAOAStage C118.1k903104.4μs
QAE Risk AnalysisQAE/IQAEStage C293.1k40153713680.4ms
QAOA MaxCutQAOAStage C131.5k1206219.6μs
Quantum ChromodynamicsTrotterStage C131.1k909320.4μs
Quantum Machine LearningSwap TestStage C153.4k18010303.6μs
Quantum OptimizationQAOAStage C131.5k1206219.6μs
Space Mission PlanningQAOAStage C157.5k1209277.2μs

Key Observations

  • Qubit range: 1.8k (QEC) to 401k (Materials) 230x variation across problems
  • T-gate intensive: QAE (15), HHL (12), Shor (6), Climate HHL (3) these require T-state factories
  • Rotation dominated: VQE and QAOA problems use rotations instead of T-gates simpler for near-term hardware
  • All estimates from real Azure Quantum Resource Estimator not mock data