quantumlib/Cirq
Cirq
Cirq is a Python quantum computing framework used for designing, simulating, and executing quantum circuits on Noisy Intermediate-Scale Quantum (NISQ) hardware. It serves as a quantum circuit simulator and noise modeler, as well as a tool for the implementation of quantum algorithms.
The framework provides a specialized interface for NISQ hardware, allowing users to map logical quantum circuits to physical device topologies while validating hardware connectivity and gate constraints. It distinguishes itself through integrated noise modeling, applying depolarizing and damping channels to mimic the decoherence and errors found in real quantum processors.
The project covers a broad range of capabilities, including quantum circuit design, hardware integration, and state simulation. It includes tools for gate decomposition, hardware topology mapping, and the execution of fundamental quantum procedures such as Fourier transforms and unstructured data search. Additionally, it provides analytical utilities for molecular ground state computation and hardware fidelity benchmarking.
Features
- Quantum Computing - Provides a full framework for designing, simulating, and executing quantum computing circuits and algorithms.
- Quantum Circuit Design - Provides a comprehensive framework for designing and simulating quantum circuits while accounting for noise and constraints.
- Quantum Hardware Topology Mapping - Translates quantum circuits to generic device topologies to ensure compatibility with physical qubit layouts.
- Hardware Metadata Retrievers - Retrieves technical specifications including available qubit sets, connectivity graphs, and supported gate families.
- Quantum - Defines the physical connectivity and constraints of a device to ensure circuits are compatible.
- Quantum Calibration Retrieval - Retrieves real-time hardware calibration data from external APIs to increase circuit execution accuracy.
- Quantum Hardware Interfaces - Provides a system for mapping logical quantum circuits to physical device topologies with constraint validation.
- Quantum Device Constraint Definition - Specifies unique hardware limitations and validation rules for quantum processors.
- Hardware Compatibility Validation - Verifies if quantum operations and circuits adhere to specific processor requirements and qubit connectivity.
- Hardware Constraint Validations - Provides tools to validate that quantum circuits adhere to the connectivity and gate constraints of specific hardware devices.
- Quantum Algorithm Implementation - Provides a library for building complex quantum operations through gate decomposition and circuit transformations.
- Quantum Circuit Execution - Enables the execution of quantum circuits on physical hardware and simulators to collect real-world data.
- Moment-Based Construction - Organizes quantum operations into time-sliced moments to handle scheduling and qubit disjointness.
- Noise and Measurement Emulation - Simulates hardware imperfections using amplitude damping and depolarizing noise channels to model decoherence.
- Quantum Circuit Transpilation - Transforms abstract quantum circuits into hardware-compatible versions through custom routing and modifications.
- Unitary Gate Applications - Executes single- and multi-qubit operations to modify quantum states within a circuit.
- Quantum Simulators - Models quantum state evolution and hardware noise to predict circuit behavior on classical hardware.
- Density Matrix Simulators - Implements state simulation using density matrices to model mixed states and the effects of decoherence.
- Mixed State Simulations - Uses density matrices to simulate noisy circuits and represent all possible outcomes of a system.
- Hardware Emulations - Simulates quantum circuits with integrated noise models and device constraints to predict behavior on physical processors.
- Noise Modeling - Provides a simulation environment that mimics physical hardware decoherence and errors using depolarizing and damping channels.
- Unitary Gate Decompositions - Decomposes complex unitary operations into simpler gates supported by target quantum hardware.
- NISQ Algorithm Development - Supports implementing and testing quantum algorithms on Noisy Intermediate-Scale Quantum hardware.
- Quantum Observable Calculation - Constructs measurement operators from sums and products of strings to extract physical properties from states.
- Quantum Noise Channel Models - Mimics physical hardware imperfections using amplitude damping and depolarizing noise channels.
- Qubit Mapping Systems - Provides systems for mapping logical qubits to physical hardware based on device connectivity and coordinates.
- Quantum Noise Visualizations - Generates heatmaps to plot noise characteristics and error rates across a grid of quantum components.
- Quantum Parameter Optimizations - Finds optimal quantum control parameters by iterating through combinations to minimize a defined cost function.
- Quantum Optimization Analysis - Evaluates approximate optimization algorithms through landscape analysis, optimization paths, and precomputed angles.
- Quantum Backend Integrations - Connects to third-party simulation backends to handle deeper circuits or specific optimization needs.
- Quantum Hardware Experimentation - Deploys quantum circuits to physical processors to run end-to-end experiments and collect data.
- Cost Hamiltonian Expectation Calculations - Estimates the expectation value of a cost function by sampling the output of a parameterized circuit.
- Quantum - Performs a transform or its inverse on qubits to shift between time and frequency domains.
- Quantum Eigenvalue Estimation - Approximates eigenvalues of a unitary operator using controlled operations and inverse Fourier transforms.
- Distributed Quantum Simulations - Distributes high-qubit circuit simulations across multiple compute nodes to increase execution speed.
- Constraint Validations - Checks if quantum circuits adhere to the connectivity and operational rules of a specific device.
- Optimization Circuit Implementations - Implements approximate optimization circuits like QAOA to solve complex combinatorial problems.
- Quantum State Transmission - Moves a state from one qubit to another using entangled states and classical communication.
- Register Definitions - Creates sets of qubits using abstract names or lattices to act as targets for quantum operations.
- Subcircuit Nesting - Embeds frozen circuits within other circuits to reduce duplication and support complex remapping.
- Custom Gate Syntheses - Enables the creation of specialized quantum operations using unitary matrices or decomposition into simpler gates.
- Matrix Extractions - Computes the matrix representation of gates or circuits to analyze their mathematical effects.
- State Vector Extractions - Provides the ability to extract the complete state vector after execution for debugging and detailed analysis.
- Quantum Chemistry Simulations - Determines the lowest energy state of a system using variational principles and trial wavefunctions.
- Quantum Search Algorithms - Finds a marked bitstring within a register using an oracle and iterative amplitude amplification.
- Quantum State Visualizations - Generates histograms from sampled data to analyze the distribution of observed quantum states.
- Quantum Subcircuit Nesting - Supports embedding pre-defined circuits within larger ones to simplify repetitive quantum patterns.
- Quantum Timing Scheduling - Organizes quantum operations into discrete time slices to manage simultaneous execution and timing.
- Quantum Parameter Sweeps - Evaluates multiple circuit variations by sweeping operation parameters to optimize quantum performance.
- Symbolic Gate Translation - Rewrites complex quantum gates into target-specific instruction sets supported by hardware.
- Pluggable Execution Backends - Allows switching between internal classical simulators and external high-performance quantum compute engines.
- Distributed Observability Simulations - Renders simulation results as a distribution of basis states to analyze the probability of different outcomes.
- Quantum Fidelity Benchmarking - Measures device performance using cross-entropy benchmarking to characterize systemic quantum errors.
- Pre-Deployment Hardware Simulation - Provides software emulation of hardware constraints and noise to verify quantum circuit logic before physical deployment.
- Quantum Computing - Framework for creating and invoking noisy quantum circuits.
- Development Frameworks - Library for writing and optimizing NISQ-era quantum circuits.
- Quantum Computing - Hardware-aware quantum circuit design for NISQ devices.
- Quantum Programming Frameworks - Framework for creating and invoking NISQ-era circuits.
