Steven GellerQuantum Computing, End to End

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    Publication record

    Quantum computing labs

    Implementation-focused chapters and the reproducibility standard for future standalone quantum computing labs and notebooks.

    Current status

    80 companion artifact entries resolve to local source and a downloadable verification fixture in this publication build.

    Download the companion package

    The downloadable archive uses fixed timestamps for reproducible packaging and includes the tested Python package, its test suite, and eight pre-executed notebooks. Verify the archive against the separately published SHA-256 file before use.

    Download labs 0.1.0 (.zip)SHA-256 checksum

    Recorded verification

    Result
    pass
    Tests
    13
    Runtime
    CPython 3.13.7
    Recorded
    2026-08-14T05:08:38+00:00
    Command
    python -m unittest discover -s tests -v

    This is a checked-in run record, not a claim that tests execute in every reader environment.

    Executable notebooks in the archive

    Eight pre-executed Jupyter notebooks exercise the same versioned Python modules as the test suite. Stored output is compared byte-for-byte with a fresh isolated execution during release QA.

    Companion artifacts

    Implementation chapters

    Python and Quantum Programming WorkflowA reproducible Python workflow for quantum experiments: pinned environments, runnable tests, run records, and the line between stable ideas and drifting SDKs.Open chapter →Building a Small Simulator From ScratchBuild a minimal statevector simulator in Python: normalization, unitary gates, basis ordering, Born-rule sampling, and the tests that catch wrong mental models.Open chapter →Qiskit, Primitives, and Circuit ExecutionQiskit-style circuit execution: primitives, backends, shot counts and standard error, transpilation metadata, and the debugging ladder to hardware.Open chapter →Cirq and Alternative ToolchainsComparing quantum SDKs by circuit model, simulator behavior, backend fit, API stability, and reproducibility rather than popularity.Open chapter →Transpilation and Hardware-Aware CompilationHow transpilation rewrites circuits for real gate sets and topologies: routing overhead, compiled depth, error budgets, and checkable claims.Open chapter →Noise Models and Noisy SimulationNoise models and noisy simulation: bit-flip and depolarizing channels, ideal-versus-noisy comparison, and diagnosing error patterns.Open chapter →Benchmarking Quantum ProgramsHow to benchmark quantum programs honestly: baselines first, shot-noise arithmetic, explicit evidence labels, and artifacts anyone can rerun.Open chapter →Resource Estimation for Fault-Tolerant AlgorithmsTurn a logical quantum workload into auditable physical-qubit and runtime estimates, with sensitivity analysis that exposes the dominant assumption.Open chapter →Reproducible Quantum LabsPackage quantum experiments so anyone can rerun them: exact commands, seeds, expected outputs, shot statistics, failure modes, and honest limitations.Open chapter →

    Lab evidence standard

    A standalone lab should record its environment, exact command, dependency versions, seed where randomness matters, expected output, classical baseline, and known limitation. A visible Lab or Notebook action appears on a chapter only when its declared local source resolves.