autoresearch-quantum/configs/rungs/rung2.yaml

74 lines
1.8 KiB
YAML
Raw Normal View History

rung: 2
name: "Backend-Aware Stability Rung"
description: "Same [[4,2,2]] task, but with repeated cheap-tier runs, backend variation, and stronger stability pressure."
objective: "Favor experiment settings that hold score under calibration-like backend changes and repeated noisy evaluation."
bootstrap_incumbent:
seed_style: h_p
encoder_style: cx_chain
verification: both
postselection: all_measured
ancilla_strategy: dedicated_pair
optimization_level: 3
layout_method: sabre
routing_method: sabre
approximation_degree: 1.0
target_backend: fake_kyoto
noise_backend: fake_kyoto
shots: 768
repeats: 3
notes: "Stability-focused bootstrap incumbent."
search_space:
max_challengers_per_step: 8
dimensions:
target_backend: [fake_kyoto, fake_brisbane, fake_sherbrooke]
noise_backend: [fake_kyoto, fake_brisbane, fake_sherbrooke]
verification: [both, z_only]
postselection: [all_measured, z_only]
optimization_level: [1, 2, 3]
layout_method: [sabre, dense]
routing_method: [sabre, basic]
tier_policy:
cheap_margin: 0.001
confirmation_margin: 0.0
cheap_shots: 768
expensive_shots: 1536
cheap_repeats: 3
expensive_repeats: 1
promote_top_k: 2
enable_hardware: false
confirm_incumbent_on_hardware: true
hardware_budget: 1
score:
name: weighted_acceptance_cost
base_cost: 1.0
cheap_quality:
noisy_fidelity: 0.30
logical_witness: 0.25
codespace_rate: 0.20
stability_score: 0.20
spectator_alignment: 0.05
expensive_quality:
logical_witness: 0.45
codespace_rate: 0.15
stability_score: 0.30
spectator_alignment: 0.10
cost_weights:
two_qubit_count: 0.06
depth: 0.01
shot_count: 0.00025
runtime_estimate: 0.02
queue_cost_proxy: 0.35
step_budget: 3
patience: 2
hardware:
backend_name:
channel:
instance:
token_env_var: QISKIT_IBM_TOKEN