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Amplitude Amplification

An open source quantum machine learning and simulation framework that accelerates the path from theoretical algorithms to practical, executable quantum circuit synthesis.

Amplitude Amplification (ampamp) provides a robust, production-grade API for researchers and engineers building next-generation quantum solutions. Whether you are generating optimal polynomial sequences via Quantum Singular Value Transformation (QSVT), mapping out oblivious operator expansions, or deploying partitioned distributed quantum searches, ampamp ensures exact phase tracking and high-fidelity algorithmic representation.

Ecosystem At A Glance

  • Foundations

    Standard Grover's Search algorithms. Contains precise analytical definitions of the Soufflé Problem, diffusion operators, and exact success probability tracking.

    API Reference

  • Fixed-Point Search (FPAA)

    Achieve monotonic algorithmic convergence. Leverages monotonic Chebyshev-derived phase schedules to safely amplify target states without precise knowledge of target counts.

    API Reference

  • QSVT & SU(2) Calculus

    A complete engine for Quantum Singular Value Transformations via \(SU(2)\) homomorphisms. Extract SVD mappings natively on quantum operators with mathematically verified parity models.

    API Reference

  • Distributed AA

    Scalable search space partitioning mechanisms engineered for classical-quantum distributed processing clusters and NISQ-era parallelization networks.

    API Reference

  • Oblivious Amplification (OAA)

    Robust block-encoding arrays and operator amplification capabilities for Oblivious algorithmic structures utilizing pristine Linear Combination of Unitaries (LCU) architectures.

    API Reference

  • Variable Time (VTAA)

    Variable-Time Amplitude Amplification branch systems mapping algorithmic costs to multi-staged state circuits ensuring asymptotic \(O(\sqrt{E[t^2]})\) expected runtime scaling.

    API Reference

  • FPOA

    Fixed-Point Oblivious Amplitude Amplification defining discrete \(SU(2)\) non-linear recurrence paths to mitigate over-rotation faults in Hamiltonian simulations.

    API Reference

  • Algorithm Diagnostics

    An extensive suite of independent hardware realism auditors. Verify block unitarity constraints, map phase damping trajectories, limit-test empirical bounding box ranks, and identify algorithmic fidelity collapse.

    API Reference

Quick Start

Get started quickly by bringing ampamp into your Python environment locally.

pip install -e .

Instantiate precision-tuned engines capable of scaling to highly complex quantum states:

from ampamp import FPAAAuditor, FixedPointEngine

# Establish a 15-iteration strictly monotonic Chebyshev schedule
engine = FixedPointEngine(L=15, delta=1e-3)

# Access the classical analytical hardware limits
auditor = FPAAAuditor(engine)
auditor.estimate_ftqc_cost(synthesis_epsilon=1e-4)

# Generate the synthesized circuit structure to inject directly into Qiskit primitives
circuit = engine.build_fixed_point_circuit(num_qubits=6, marked_indices=[2, 7])