quantum-practices

In the author's own words, from each skill's SKILL.md — showing the first 30 of 60 files.

• quantum-skills

  Root entrypoint for the quantum-skills package. Use this skill to route requests to the correct simulator or algorithm sub-skill, enforce full skill-chain reading before coding, and avoid duplicating implementation details that are already defined in leaf skills.

  SKILL.md on GitHub (opens in a new tab)

• algorithms

  A top-level index of quantum algorithms centered on the UnitaryLab implementation, covering quantum primitives, linear systems, cryptography, Hamiltonian simulation, Schrodingerization, quantum machine learning, eigensolvers, gradients, and quantum error correction, with selected Qiskit, PennyLane, and Classiq examples included as reference extensions. Skill-first for covered code generation, run…

  algorithms/SKILL.md on GitHub (opens in a new tab)

• simulators

  A collection of quantum simulators for quantum program development, providing local and cloud execution environments. Includes UnitaryLab (recommended), Qiskit, and PennyLane for various use cases and capabilities.

  simulators/SKILL.md on GitHub (opens in a new tab)

• cryptography

  Quantum algorithms that attack classical cryptographic protocols, including Shor's integer factorization, Shor-style discrete logarithm solving with two-register Fourier sampling, and Simon's hidden subgroup problem. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/cryptography/SKILL.md on GitHub (opens in a new tab)

• eigensolvers

  Quantum eigensolver algorithms for operator spectrum estimation, covering exact classical diagonalization with NumPyEigensolver and variational excited-state solving with VQD. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/eigensolvers/SKILL.md on GitHub (opens in a new tab)

• gradients

  Master routing guide for all quantum gradient and geometric tensor methods in this folder. Read this file first, then follow the leaf skill for the chosen method. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/gradients/SKILL.md on GitHub (opens in a new tab)

• hamiltonian-simulation

  Quantum Hamiltonian simulation methods for approximating time evolution e^{-iHt}. Includes Trotter-Suzuki decomposition, QDrift randomized sampling, Cartan decomposition, QSP-HS polynomial spectral transformation, and Taylor series LCU expansion. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/hamiltonian-simulation/SKILL.md on GitHub (opens in a new tab)

• linear-systems

  A set of quantum algorithms for solving linear systems of equations and related Fourier/signal-processing subroutines. This skill includes UnitaryLab implementations and educational resources for HHL, LCU, AQC, QFT, the basic single-qubit QSP demo, QSVT-QLSA, and VQLS. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/linear-systems/SKILL.md on GitHub (opens in a new tab)

• primitives

  A collection of fundamental quantum computing primitives implemented using UnitaryLab, including basic gates, state preparation techniques, and measurement protocols. Provides efficient implementations and educational resources for understanding and utilizing quantum primitives in algorithm development. Skill-first for covered code generation, runnable examples, execution, debugging, validation,…

  algorithms/primitives/SKILL.md on GitHub (opens in a new tab)

• quantum-error-correction

  A clear and practical skill guide for learning and running a PennyLane-based qLDPC tutorial, from classical LDPC basics to CSS and Hypergraph Product code construction. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/quantum-error-correction/SKILL.md on GitHub (opens in a new tab)

• quantum-machine-learning

  Variational quantum algorithms for optimization and machine learning, including QAOA for combinatorial optimization, VQE for ground-state energy estimation, Fermi-Hubbard VQE for lattice models, VQC for supervised learning, QCBM for generative modeling, and CVQNN for continuous-variable workflows. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fi…

  algorithms/quantum-machine-learning/SKILL.md on GitHub (opens in a new tab)

• schrodingerization

  Quantum PDE solvers using Schrodingerization, transforming non-unitary PDEs into unitary Schrodinger-type dynamics for quantum simulation. Currently covers advection and heat equations in 1D/2D. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/schrodingerization/SKILL.md on GitHub (opens in a new tab)

• state-preparation

  A router for UnitaryLab quantum state-preparation algorithms, including sparse-support, uniformly controlled-rotation, tensor-network, recursive multiplexer, and variational Pauli-word preparation. Use when selecting or comparing methods for loading target amplitude vectors into quantum circuits.

  algorithms/state-preparation/SKILL.md on GitHub (opens in a new tab)

• pennylane

  PennyLane - A versatile quantum machine learning library that supports hybrid quantum-classical computations.

  simulators/pennylane/SKILL.md on GitHub (opens in a new tab)

• qiskit

  A collection of quantum algorithms implemented using Qiskit, covering a wide range of topics including quantum search, quantum phase estimation, amplitude amplification, and more. Provides efficient implementations and examples for various quantum computing applications.

  simulators/qiskit/SKILL.md on GitHub (opens in a new tab)

• unitarylab

  Use UnitaryLab for local quantum circuit construction, simulation, measurement, expectation values, transpilation, drawing, serialization, and algorithms provided by unitarylab.library. Trigger for runnable UnitaryLab workflows; consult bundled references for package APIs and dedicated algorithm skills for algorithm-specific workflows.

  simulators/unitarylab/SKILL.md on GitHub (opens in a new tab)

• discretelog

  Use when users ask about solving the discrete logarithm problem g^x ≡ y (mod P) with Shor-style two-register Fourier sampling, building/explaining DLP circuits, running simulator demos, or debugging post-processing (continued fractions plus two-dimensional Fourier-sample congruence solving). Triggers: discrete log, DLP, Shor discrete logarithm, g^x mod P, modular exponentiation, two-dimensional F…

  algorithms/cryptography/discretelog/SKILL.md on GitHub (opens in a new tab)

• shor

  Use this skill when the user asks for Shor integer factorization, quantum order-finding, period estimation, or implementing/running/debugging ShorAlgorithm in this repository (especially matrix/operator methods, IQFT-based phase post-processing, and continued-fraction period recovery). Keywords: shor, factor N, order finding, period finding, modular exponentiation, continued fraction, quantum fac…

  algorithms/cryptography/shor/SKILL.md on GitHub (opens in a new tab)

• simon

  Use for implementing, explaining, running, or debugging Simon's algorithm in this repository, especially for oracle construction, measurement interpretation, GF(2) post-processing, simulator state extraction, and compatible reimplementation. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/cryptography/simon/SKILL.md on GitHub (opens in a new tab)

• numyeigensolver

  Exact classical eigensolver for quantum operators using NumPy and SciPy backends, with optional auxiliary operator evaluation and eigenpair filtering. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/eigensolvers/numyeigensolver/SKILL.md on GitHub (opens in a new tab)

• vqd

  Variational Quantum Deflation (VQD) eigensolver for computing the lowest excited states of a quantum operator with Qiskit primitives. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/eigensolvers/vqd/SKILL.md on GitHub (opens in a new tab)

• finite-difference

  Quantum gradient estimation via finite difference method. Supports both Estimator (expectation value gradients) and Sampler (probability distribution gradients) primitives with central, forward, and backward difference schemes. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/gradients/finite-difference/SKILL.md on GitHub (opens in a new tab)

• linear-combination

  Analytic quantum gradient and Quantum Geometric Tensor (QGT) estimation via linear combination of unitaries (LCU). Supports Estimator (expectation value gradients), Sampler (probability distribution gradients), and QGT primitives with configurable derivative types. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/gradients/linear-combination/SKILL.md on GitHub (opens in a new tab)

• parameter-shift

  Analytic quantum gradient estimation via the parameter shift rule. Supports both Estimator (expectation value gradients) and Sampler (probability distribution gradients) primitives. Requires circuits composed exclusively of supported gate types. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/gradients/parameter-shift/SKILL.md on GitHub (opens in a new tab)

• qfi

  Compute the Quantum Fisher Information (QFI) matrix for a pure parameterized quantum state using the Quantum Geometric Tensor (QGT). Extracts the real part of the QGT and scales it by 4. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/gradients/qfi/SKILL.md on GitHub (opens in a new tab)

• reverse

  Reverse-mode statevector gradient and QGT computation for parameterized circuits using Qiskit Algorithms classes ReverseEstimatorGradient and ReverseQGT. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/gradients/reverse/SKILL.md on GitHub (opens in a new tab)

• spsa

  Concise guide to the local SPSA estimator and sampler gradient implementations for parameterized quantum circuits. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/gradients/spsa/SKILL.md on GitHub (opens in a new tab)

• cartan

  Simulate the time evolution of a quantum system using Cartan decomposition. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/hamiltonian-simulation/cartan/SKILL.md on GitHub (opens in a new tab)

• qdrift

  QDrift randomized Hamiltonian simulation, approximating e^{-iHt} by stochastically sampling Pauli-term evolutions with probability proportional to coefficient magnitude. Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/hamiltonian-simulation/qdrift/SKILL.md on GitHub (opens in a new tab)

• qsp

  QSP-HS: QSP-based Hamiltonian simulation for approximating e^{-iHt} by block-encoding a Hamiltonian and applying polynomial spectral transformations. Use the basic QSP demo skill instead for single-qubit scalar QSP examples such as cos(t*x). Skill-first for covered code generation, runnable examples, execution, debugging, validation, and fixed workflows.

  algorithms/hamiltonian-simulation/qsp/SKILL.md on GitHub (opens in a new tab)

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