unitarylab
@unitarylab Organization
Public Skills
taylor
by unitarylab
"Simulate the time evolution of a quantum system using Taylor series expansion."
hamiltonian-simulation
by unitarylab
Quantum Hamiltonian simulation methods for approximating time evolution e^{-iHt}. Includes Trotter-Suzuki decomposition, QDrift randomized sampling, Cartan decomposition, QSP polynomial spectral transformation, and Taylor series LCU expansion.
cartan
by unitarylab
"Simulate the time evolution of a quantum system using Cartan decomposition."
discretelog
by unitarylab
"Use when users ask about solving the discrete logarithm problem g^x ≡ y (mod P) with Shor's quantum algorithm, building/explaining DLP circuits, running simulator demos, or debugging post-processing (continued fractions, order recovery, congruence solving). Triggers: discrete log, DLP, Shor discrete logarithm, g^x mod P, modular exponentiation, continued fractions, quantum cryptography demo."
shor
by unitarylab
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 factoring, ShorAlgorithm.
qsp
by unitarylab
QSP-based Hamiltonian simulation approximates e^{-iHt} by block-encoding the Hamiltonian and applying polynomial spectral transformations via interleaved signal-processing rotations, achieving high precision with efficiently bounded circuit depth.
unitarylab
by unitarylab
UnitaryLab is a quantum computing framework for education and research. It offers a simple interface for building and simulating quantum circuits, making it suitable for learning, teaching, and experimenting with quantum algorithms.
simon
by unitarylab
"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."
qdrift
by unitarylab
QDrift randomized Hamiltonian simulation, approximating e^{-iHt} by stochastically sampling Pauli-term evolutions with probability proportional to coefficient magnitude.
trotter
by unitarylab
Trotter-Suzuki product-formula Hamiltonian simulation, approximating e^{-iHt} via structured short-time exponential products with controllable order and step count.
hhl
by unitarylab
A quantum algorithm for solving linear systems of equations, providing exponential speedup over classical methods for certain types of problems. This skill includes efficient implementations and educational resources for understanding and utilizing quantum linear systems algorithms in various applications.
lcu
by unitarylab
A quantum algorithm for solving linear systems of equations using the Linear Combination of Unitaries (LCU) method, providing exponential speedup over classical methods for certain types of problems. This skill includes efficient implementations and educational resources for understanding and utilizing the LCU algorithm in various applications.
quantum-signal-processing
by unitarylab
A quantum algorithm for signal processing tasks, leveraging quantum phase estimation and amplitude amplification techniques to achieve efficient signal analysis and transformation. This skill includes implementations and educational resources for understanding and utilizing quantum signal processing algorithms in various applications.
amplitude-amplification
by unitarylab
A quantum algorithm that generalizes Grover's search algorithm, allowing for the amplification of the probability of desired outcomes in a quantum state. It is used to find marked items in an unsorted database with quadratic speedup compared to classical algorithms. This skill provides a comprehensive guide to understanding, implementing (using UnitaryLab's quantum simulator), and utilizing amplitude amplification in quantum computing applications.
amplitude-estimation
by unitarylab
A quantum algorithm for estimating the amplitude of a specific state in a quantum superposition, which can be used for various applications such as Monte Carlo simulations and optimization problems. Provides efficient implementations and educational resources for understanding and utilizing amplitude estimation in quantum algorithm development.
hadamard-test
by unitarylab
A quantum algorithm that uses the Hadamard test to estimate the expectation value of a unitary operator with respect to a given quantum state. This algorithm is fundamental in quantum computing and has applications in various quantum algorithms, including quantum phase estimation and variational quantum algorithms.
hadamard-transform
by unitarylab
A quantum algorithm for performing the Hadamard transform, which is a fundamental operation in quantum computing that creates superposition states. This skill includes efficient implementations and educational resources for understanding and utilizing the Hadamard transform in various quantum algorithms and applications.
heat-2d-schrodingerization
by unitarylab
A quantum-compatible solver for the 2D Heat Equation using Schrödingerization to transform the non-unitary diffusion equation into a unitary evolution problem. Supports anisotropic diffusion, Dirichlet and periodic boundary conditions, source terms, and both classical and Trotter-based quantum evolution with automatic 2D circuit generation and 3D temperature field visualization.
quantum-phase-estimation
by unitarylab
A quantum phase estimation algorithm that can estimate the eigenvalues of a unitary operator with high precision, which is a fundamental component in many quantum algorithms such as Shor's algorithm and quantum simulation.
qaoa
by unitarylab
Skill for understanding, using, and implementing the Quantum Approximate Optimization Algorithm (QAOA) for Max-Cut problems via the QAOAAlgorithm class.
qcbm
by unitarylab
Skill for understanding, using, and implementing the Quantum Circuit Born Machine (QCBM) for learning discrete probability distributions (Bars-and-Stripes) via the QCBMAlgorithm class.
qnn
by unitarylab
Skill for understanding, using, and implementing the Quantum Neural Network (QNN) with parameterized quantum circuits for supervised learning via the QNNAlgorithm class.
vqc
by unitarylab
Skill for understanding, using, and implementing the Variational Quantum Classifier (VQC) for Iris dataset classification with data re-uploading and Parameter Shift Rule via the VQCAlgorithm class.
vqe
by unitarylab
Skill for understanding, using, and implementing the Variational Quantum Eigensolver (VQE) for finding the ground state energy of the 2-qubit Ising Hamiltonian via the VQEAlgorithm class.
pennylane
by unitarylab
PennyLane - A versatile quantum machine learning library that supports hybrid quantum-classical computations.
quantum-error-correction
by unitarylab
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.
quantum-skills
by unitarylab
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.
algorithms
by unitarylab
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.
numyeigensolver
by unitarylab
Exact classical eigensolver for quantum operators using NumPy and SciPy backends, with optional auxiliary operator evaluation and eigenpair filtering.
vqd
by unitarylab
Variational Quantum Deflation (VQD) eigensolver for computing the lowest excited states of a quantum operator with Qiskit primitives.
eigensolvers
by unitarylab
Quantum eigensolver algorithms for operator spectrum estimation, covering exact classical diagonalization with NumPyEigensolver and variational excited-state solving with VQD.
finite-difference
by unitarylab
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.
linear-combination
by unitarylab
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.
gradients
by unitarylab
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.
parameter-shift
by unitarylab
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.
qfi
by unitarylab
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.
reverse
by unitarylab
Reverse-mode statevector gradient and QGT computation for parameterized circuits using Qiskit Algorithms classes ReverseEstimatorGradient and ReverseQGT.
quantum-fourier-transform
by unitarylab
Skill for implementing and using the Quantum Fourier Transform (QFT) via the PennyLane QFT operation. Covers circuit construction, gate decomposition, matrix access, adjoint (inverse QFT), and integration into larger circuits such as QPE and Shor's algorithm.
numpy-minimum-eigensolver
by unitarylab
NumPyMinimumEigensolver skill for deterministic minimum-eigenvalue computation in qiskit_algorithms.minimum_eigensolvers.
spsa
by unitarylab
Concise guide to the local SPSA estimator and sampler gradient implementations for parameterized quantum circuits.
advection-schrodingerization
by unitarylab
A Schrödingerization-based solver for the 1D advection equation, supporting both direct unitary evolution (under periodic and central difference discretization) and general transformation for non-unitary cases. Enables classical and quantum simulation through Hamiltonian formulation.
backward-heat-1d-schrodingerization
by unitarylab
A Schrödingerization-based solver for the 1D backward heat equation, addressing its ill-posed nature by transforming unstable exponential growth into a structured evolution system. Supports classical matrix methods and quantum-inspired Trotter simulation.
quantum-machine-learning
by unitarylab
Variational quantum algorithms for optimization and machine learning, including QAOA for combinatorial optimization, VQE for ground-state energy estimation, QNN and VQC for supervised learning with parameterized quantum circuits, and QCBM for generative modeling of discrete probability distributions.
schrodingerization
by unitarylab
Quantum PDE solvers using Schrodingerization, transforming non-unitary PDEs into unitary Schrodinger-type dynamics for quantum simulation. Currently covers advection, backward heat, and heat equations in 1D/2D.
qiskit
by unitarylab
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
by unitarylab
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.
cryptography
by unitarylab
Quantum algorithms that attack classical cryptographic protocols, including Shor's integer factorization, discrete logarithm solving, and Simon's hidden subgroup problem.
linear-systems
by unitarylab
A set of quantum algorithms for solving linear systems of equations, providing exponential speedup over classical methods for certain types of problems. This skill includes efficient implementations and educational resources for understanding and utilizing quantum linear systems algorithms in various applications.
primitives
by unitarylab
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.
heat-1d-schrodingerization
by unitarylab
A quantum-compatible solver for the 1D Heat Equation using Schrödingerization to transform the non-unitary diffusion equation into a unitary evolution problem. Supports Dirichlet and periodic boundary conditions, source terms, and both classical and Trotter-based quantum evolution with automatic circuit generation and solution visualization.