UnitaryLab
Official@unitarylab
Offers a comprehensive framework for designing, simulating, and executing quantum circuits, algorithms, and differential equation solvers across diverse hardware backends.
Agent Skills by UnitaryLab
Showing 35 vetted skills indexed across 1 GitHub repositories.
unitarylabquantum-skills
Route quantum inquiries to leaf Skills and load full Skill-chains before coding.
unitarylabsimulators
Select quantum simulators across UnitaryLab, Qiskit, and PennyLane backends.
unitarylabalgorithms
Organize quantum algorithm demos with YAML frontmatter and Markdown instructions.
unitarylabqiskit
Design, simulate, and execute quantum circuits across multiple backends with Qiskit.
unitarylabunitarylab
Design and simulate quantum circuits with GateSequence across UnitaryLab, Qiskit, and PennyLane.
unitarylabpennylane
Enable differentiable quantum circuits and hybrid quantum-classical workflows in Python.
unitarylabpennylaneqldpc
Run PennyLane qLDPC tutorials covering LDPC basics, CSS construction, and Hypergraph Product validation.
unitarylabquantum-machine-learning
Document variational quantum machine learning algorithms with SKILL.md files and runnable scripts.
unitarylabcryptography
Apply quantum phase estimation and period finding to analyze cryptographic primitives.
unitarylabhamiltonian-simulation
Simulate quantum time evolution under Hamiltonians with Trotter-Suzuki and QDrift methods.
unitarylabprimitives
Automate creation and understanding of quantum primitives with Python and UnitaryLab.
unitarylablinear-systems
Solve linear systems with HHL, LCU, and QSP quantum algorithms.
unitarylabbackward-heat-1d-schrodingerization
Solve 1D backward heat PDEs via warped phase transformation.
unitarylabvqe
Estimate ground-state energies for 2-qubit Ising Hamiltonians using VQE with COBYLA.
unitarylabvqc
Train a variational quantum classifier on tabular data with parameter-shift gradients.
unitarylabqcbm
Train a quantum circuit Born machine on Bars-and-Stripes distributions with KL-divergence and parameter-shift gradients.
unitarylabqaoa
Solve Max-Cut problems with QAOA circuits using COBYLA optimization.
unitarylabqnn
Build and train a Quantum Neural Network for supervised classification with angle-encoded PQCs.
unitarylabsimon
Run Simon's algorithm on quantum circuits to recover hidden bitstrings.
unitarylabdiscretelog
Solve discrete logarithms g^x ≡ y (mod P) with quantum period-finding.
unitarylabshor
Factor composite integers via quantum period finding and classical post-processing.
unitarylabtrotter
Decompose Hamiltonians into Pauli terms and generate Trotter-Suzuki circuits.
unitarylabqdrift
Sample Pauli-term evolutions to approximate e^{-iHt} for quantum Hamiltonians.
unitarylabhadamard-test
Estimates expectation values and overlaps using Hadamard and swap tests.
Frequently Asked Questions About UnitaryLab
FAQPage SchemaWhat specific tasks can researchers perform using UnitaryLab?▼
Researchers can design and simulate quantum circuits, execute variational algorithms like VQE and QAOA, perform Hamiltonian time evolution, and solve complex partial differential equations using Schrödingerization techniques across multiple backends.
Which technical personas benefit most from these quantum capabilities?▼
Quantum physicists, computational scientists, and researchers focused on variational circuit design or numerical analysis will find these resources essential for prototyping and validating quantum-classical hybrid approaches.
What are the primary dependencies for running these quantum simulations?▼
Execution requires a local environment configured with Qiskit or PennyLane backends. Users must manage circuit dependencies and ensure compatible hardware or simulator interfaces are installed to support the specific gate-level operations defined in the manifest.