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Qiskit avatar

Qiskit/qiskit

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7,522 stars·2,943 forks·Python·Apache-2.0·5 vueswww.ibm.com/quantum/qiskit↗

Qiskit

Qiskit is a quantum computing software development kit used for designing, simulating, and executing quantum circuits on physical hardware and simulators. It functions as a quantum algorithm framework, a circuit simulator, and a vendor-agnostic hardware interface for dispatching workloads across diverse providers.

The project features a quantum circuit transpiler that optimizes abstract designs to match the specific basis gates and qubit connectivity of target hardware. It employs a pass-based transpilation pipeline and symbolic instruction translation to convert high-level circuits into hardware-compatible versions.

The system covers a broad range of capabilities, including quantum algorithm development, state preparation, and circuit construction. It provides tools for quantum analysis such as outcome sampling, expectation value estimation, and error mitigation, alongside support for hybrid workload execution across distributed classical and quantum resources.

Features

  • Quantum Computing - Serves as a comprehensive software framework for designing, simulating, and executing quantum computing circuits and algorithms.
  • Quantum Circuit Design - Optimizes and transforms quantum circuit designs to reduce gate counts for hardware execution.
  • Hardware Dispatchers - Implements a backend-agnostic plugin system to route quantum workloads to diverse hardware providers.
  • Hardware-Aware Quantum Optimization - Reduces gate counts and improves processing speed by applying low-level optimizations tailored for specific hardware backends.
  • Quantum Development Frameworks - Provides tools for designing and implementing complex quantum routines using modular building blocks.
  • Multi-Pass Compiler Pipelines - Transforms abstract circuits into hardware-compatible versions through a sequence of analysis and optimization passes.
  • Hardware-Targeted Transpilation - Rewrites circuits to match the specific basis gates and qubit connectivity of a target device.
  • Hardware-Agnostic Execution - Runs quantum workloads on physical processors or simulators using a vendor-agnostic execution layer.
  • Circuit Depth Optimization - Transpiles circuits to reduce depth and complexity to increase fidelity before execution on hardware.
  • Quantum Circuit Execution - Provides the ability to execute quantum circuits on physical processors and simulators using standardized primitives.
  • Quantum Circuit Transpilation - Transforms abstract quantum circuits into hardware-compatible versions through a pipeline of layout, routing, translation, and optimization.
  • Quantum Simulators - Includes tools for modeling quantum states and gate operations to estimate expectation values on classical hardware.
  • Quantum Connectivity Routing - Inserts swap gates to ensure two-qubit operations occur on hardware qubits that share a physical connection.
  • Quantum Error Mitigation Frameworks - Applies noise suppression and post-processing techniques to refine raw measurement data from noisy hardware.
  • Qubit Mapping Systems - Assigns virtual qubits to physical hardware by modeling connectivity graphs and device width constraints.
  • Virtual Qubit Mapping - Assigns virtual qubits to physical hardware and expands circuits with ancillas to match target device width.
  • Backend-Agnostic Execution Layers - Provides an abstraction layer that interfaces with various computers or simulators to run quantum workloads.
  • Quantum Computing Resources - Standardizes the control and allocation of quantum computing resources across diverse hardware and simulation environments.
  • Hardware Capability Modeling - Models instruction sets, qubit properties, and connectivity graphs to inform the circuit compilation process.
  • Custom Transpilation Pipelines - Enables the construction of sequences of analysis and transformation passes to modify circuits according to project needs.
  • Hybrid Quantum-Classical Computing - Executes tasks across distributed quantum and classical resources in multi-cloud or supercomputing environments.
  • Quantum Outcome Sampling - Executes circuits to generate a distribution of measurement results across multiple shots for quantum analysis.
  • Quantum State Preparation - Allows applying gates to qubits to prepare specific quantum states for a program.
  • Quantum Error Mitigation - Applies suppression and post-processing techniques to reduce hardware noise and improve the fidelity of results.
  • Quantum Research Toolkits - Provides an environment for running workloads and performing measurements to analyze quantum physics and computational principles.
  • Quantum Result Post-processing - Refines raw output from quantum executions using specialized techniques to improve data quality for specific applications.
  • Hybrid Quantum-Classical Execution - Executes tasks across distributed quantum and classical resources in multi-cloud or supercomputing environments.
  • Quantum Observable Calculation - Calculates the expected value of quantum observable operators for given quantum states.
  • Quantum Timing Scheduling - Inserts delay instructions to manage qubit idle periods and applies timing-sensitive error reduction techniques.
  • Hardware Abstraction Layers - Interfaces with simulators and physical processors through a common set of vendor-neutral primitives.
  • Quantum ISA Translation - Translates quantum gates into the specific instruction set supported by target hardware.
  • Symbolic Gate Translation - Rewrites quantum gates into target-specific instruction sets using symbolic mapping and synthesis techniques.
  • Quantum Computing - SDK for developing quantum circuits and algorithms.
  • Quantum Computing - SDK for building and running circuits on real quantum hardware.

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Questions fréquentes

Que fait qiskit/qiskit ?

Qiskit is a quantum computing software development kit used for designing, simulating, and executing quantum circuits on physical hardware and simulators. It functions as a quantum algorithm framework, a circuit simulator, and a vendor-agnostic hardware interface for dispatching workloads across diverse providers.

Quelles sont les fonctionnalités principales de qiskit/qiskit ?

Les fonctionnalités principales de qiskit/qiskit sont : Quantum Computing, Quantum Circuit Design, Hardware Dispatchers, Hardware-Aware Quantum Optimization, Quantum Development Frameworks, Multi-Pass Compiler Pipelines, Hardware-Targeted Transpilation, Hardware-Agnostic Execution.

Quelles sont les alternatives open-source à qiskit/qiskit ?

Les alternatives open-source à qiskit/qiskit incluent : quantumlib/cirq — Cirq is a Python quantum computing framework used for designing, simulating, and executing quantum circuits on Noisy… qiskit/qiskit-tutorials — This project is a quantum computing educational resource and implementation library. It provides a collection of… quipnetwork/xq-py — xq-py is a numerical quantum computing library and software emulator used to execute quantum algorithms. It functions… mit-han-lab/torchquantum — Torchquantum is a tensor-based quantum machine learning library and simulation engine that integrates parameterized… microsoft/quantum — Quantum is a quantum development framework that provides a hybrid quantum-classical workflow for coordinating… dusty-nv/jetson-inference — jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU…