Twenty-six open-source packages organized into seven functional layers — from foundational circuit types through error correction, resource planning, algorithms, and quantum networking. Every package derives from the same Fibonacci mathematical framework.
Covers the full depth of a quantum computing stack — from type definitions and simulators to networking and fault-tolerant execution — with no gaps requiring third-party glue.
Every package derives its structure, thresholds, and scaling from Fibonacci and N-nacci mathematics — the same framework that governs the classical codec and cryptography designs.
Every package is released under AGPLv3 with whitepapers and reference implementations. Commercial licensing is available for organizations that need it.
The stack is organized by function rather than by dependency order. Each layer addresses a distinct concern: foundational types, hardware portability, error reliability, resource planning, algorithmic primitives, state representation, and characterization. Packages compose freely across layers.
The shared data vocabulary for the entire stack. Defines states, gates, circuits, and measurements in a form every other package consumes.
Statevector, Clifford/stabilizer, MPS, and photonic (Gaussian Boson Sampling) simulation — with hardware transpilation, RB/XEB/GST, QASM 2.0/3.0, and pulse-level gate compilation. Eight demo programs including quantum cryptography validation. Zero Python dependency.
A uniform interface allowing any circuit in the stack to run unchanged across simulators, cloud APIs, and direct hardware backends.
Reads and writes QASM 2.0 and 3.0 — the lingua franca of quantum computing — enabling circuit exchange with Qiskit, Cirq, and published benchmark suites.
Converts logical circuits into hardware-native circuits that respect qubit connectivity constraints, gate set limitations, and QEC layout requirements.
Compiles native gates to calibrated AWG pulse schedules — DRAG leakage suppression, virtual-Z frame tracking, and Fibonacci-ns gate durations. Header-only C++, embeds in firmware.
Fibonacci-structured QEC code families — repetition codes, rotated surface codes, and concatenated surface codes — that protect logical qubits from hardware noise.
Runs logical circuits with checkpoint-and-rollback capability, catching correctable error events and replaying from the last verified state without aborting.
Runs circuits at controlled noise levels and extrapolates to the zero-noise limit — delivering better results from noisy hardware today, with no additional qubit overhead.
Identifies and salvages residual coherence from circuit outputs that fall below reuse threshold, feeding recovered quantum resources back into subsequent circuit layers.
Assigns each gate in a circuit an error allowance proportional to how critical it is — ensuring the error budget is spent where it matters most, not distributed uniformly.
Forecasts qubit count, gate depth, and ancilla requirements for a target circuit before committing to hardware time — hardware feasibility checks included.
Combines error budgeting and physical resource estimation into a single end-to-end planning pipeline — from circuit specification to hardware feasibility in one pass.
The operating environment for live quantum computation — managing logical qubit pools, T-state reserves, and decoherence monitoring as a coordinated, persistent system.
Determines eigenvalues of quantum operators using Fibonacci-structured queries — achieving the same precision as conventional methods with far fewer circuit executions.
Compiles arbitrary mathematical functions into executable quantum circuits using a recursive N-nacci decomposition strategy with logarithmically scaling circuit depth.
A hybrid quantum-classical algorithm for ground-state energy calculations, using a tribonacci shot-budget strategy that balances exploration, exploitation, and validation.
Infers quantum states from partial measurement data using Fibonacci-word graph geometry to choose which measurements to take, extracting maximum information per run.
Constructs aperiodic cluster states for measurement-based quantum computation, where all computation is performed by measuring a pre-entangled resource state.
Simulates large quantum systems using tensor network compression, scaling to hundreds of qubits where exact state-vector simulation is impossible.
Applies tensor network renormalization to analyze entanglement structure across multiple length scales simultaneously, using N-nacci coarsening ratios.
Transmits quantum state information progressively, ordering amplitudes by importance so the first portion of a stream carries a disproportionate share of total information.
Characterizes real hardware performance by running systematic benchmarking protocols — measuring gate fidelities, coherence times, and cross-talk from actual device behavior.
Building blocks for quantum communication networks: decoherence-aware qubit transmission scheduling and entanglement routing across multi-node topologies.
All packages are published under AGPLv3 — open for use, study, and modification without permission. For commercial deployment that conflicts with copyleft, a commercial license is available.