v1.1.0 — Multi-Platform Profiles

What's New

• IonQ Forte (36 qubits, trapped ion, all-to-all connectivity)
• IonQ Aria (25 qubits, trapped ion, all-to-all connectivity)
• Quantinuum H2 (56 qubits, QCCD trapped ion, all-to-all)
• Rigetti Ankaa-3 (84 qubits, tunable transmon)
• All-to-all edge generation for trapped-ion architectures
• Adaptive T1/T2 clip ranges for ion-trap timescales (seconds, not microseconds)
• 25 tests, all passing

Supported Platforms (9 profiles)

Vendor	Processor	Type
IBM	Fez, Torino, Marrakesh	Superconducting
Google	Willow	Superconducting
IonQ	Forte, Aria	Trapped Ion
Quantinuum	H2	Trapped Ion (QCCD)
Rigetti	Ankaa-3	Superconducting
(baseline)	Noisy processor	Superconducting

v1.0.0 — Lambda-Q Noise Profiler

Lambda-Q Noise Profiler v1.0.0

Quantum processor characterization via information-geometric noise coefficients.

What It Does

• Scores every qubit on a quantum processor using the Lambda-Q coefficient (derived from the quantum geometric tensor)
• Grades qubits A/B/C/F based on noise quality
• Predicts magic state cultivation readiness against Google's published 2.3×10⁻³ threshold
• Works with real IBM Quantum hardware or simulated processor profiles

Install

\\�ash
pip install lambda-q-profiler
\\

Or from source:
\\�ash
git clone https://github.com/quantumblackswan/lambda-q-profiler.git
cd lambda-q-profiler
pip install -e .
\\

Quick Start

\\�ash

Profile 5 processors with KPI summary

lambda-q-profiler --summary

Score a single processor

lambda-q-profiler --single --t1 263 --t2 152 --e1q 2.6e-4 --e2q 5.2e-3 --ro 7.5e-3
\\

What's Included

• \core.py\ — Lambda-Q computation engine (calibration + measurement modes)
• \kpis.py\ — Buyer-facing KPI summary tables
• \probes.py\ — 5 Qiskit probe circuits for live hardware
• \profiles.py\ — 5 simulated processor profiles (IBM Fez/Torino/Marrakesh, Google Willow, noisy baseline)
• \cli.py\ — Command-line interface with --single, --summary, --output\ modes
• 20 unit tests, all passing
• Apache 2.0 license + CITATION.cff for academic use

Author

Kevin Henry Miller — Q-Bond Network DeSCI DAO, LLC