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Awesome GitHub RepositoriesQuantum Circuit Design

Tools for designing and simulating quantum circuits.

Explore 17 awesome GitHub repositories matching scientific & mathematical computing · Quantum Circuit Design. Refine with filters or upvote what's useful.

Awesome Quantum Circuit Design GitHub Repositories

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • vinta/awesome-pythonvinta का अवतार

    vinta/awesome-python

    303,207GitHub पर देखें↗

    यह प्रोजेक्ट एक व्यापक, समुदाय-क्यूरेटेड निर्देशिका है जो पायथन सॉफ्टवेयर लाइब्रेरी, फ्रेमवर्क और टूल के विशाल परिदृश्य को व्यवस्थित करती है। यह पारिस्थितिकी तंत्र नेविगेशन की सुविधा के लिए और पूरे सॉफ्टवेयर विकास लाइफसाइकिल में डेवलपर खोज को गति देने के लिए डिज़ाइन किया गया एक केंद्रीकृत नॉलेज बेस है। निर्देशिका तकनीकी डोमेन द्वारा वर्गीकृत संसाधनों का एक संरचित इंडेक्स प्रदान करके खुद को अलग करती है, जो मूलभूत विकास यूटिलिटी से लेकर विशेष इंजीनियरिंग क्षेत्रों तक फैला हुआ है। यह आर्टिफिशियल इंटेलिजेंस, डेटा साइंस, वेब डेवलपमेंट और इंफ्रास्ट्रक्चर प्रबंधन सहित उच्च-स्तरीय क्षमताओं को कवर करती है, जिससे डेवलपर्स विशिष्ट तकनीकी चुनौतियों के लिए परीक्षित समाधानों की पहचान कर सकते हैं। प्रोजेक्ट में निर्भरता प्रबंधन, स्टेटिक कोड विश्लेषण और स्वचालित परीक्षण के लिए टूल सहित क्षमताओं का एक व्यापक क्षेत्र शामिल है। यह पर्सिस्टेंट डेटा स्टोरेज, क्लाउड इंफ्रास्ट्रक्चर ऑर्केस्ट्रेशन और इंटरफ़ेस डेवलपमेंट के लिए संसाधनों को भी सूचीबद्ध करता है, जो जटिल सॉफ्टवेयर सिस्टम बनाने और बनाए रखने के लिए एक एकीकृत संदर्भ प्रदान करता है।

    Design hardware-aware quantum circuits and validate logic through specialized simulation environments.

    Pythonawesomecollectionspython
    GitHub पर देखें↗303,207
  • aws/aws-cdkaws का अवतार

    aws/aws-cdk

    12,817GitHub पर देखें↗

    The AWS Cloud Development Kit is an infrastructure-as-code framework that enables developers to define and provision cloud resources using familiar programming languages. By utilizing construct-based synthesis, it translates high-level, object-oriented code into declarative templates, allowing for the automated management of complex cloud environments through a centralized, code-driven control plane. The framework distinguishes itself through its ability to model infrastructure as a dependency-aware resource graph, ensuring that components are provisioned and updated in the correct order. It

    Provides managed environments for designing and prototyping quantum computational models.

    TypeScriptawscloud-infrastructurehacktoberfest
    GitHub पर देखें↗12,817
  • boto/boto3boto का अवतार

    boto/boto3

    9,834GitHub पर देखें↗

    Boto3 is the AWS SDK for Python, providing a programmatic interface for managing and automating AWS cloud infrastructure and services. It serves as a cloud management API client and resource manager for provisioning, configuring, and scaling virtual servers, databases, and storage. The library enables the implementation of infrastructure-as-code through declarative templates and scripts, allowing for the deployment of identical resource stacks across multiple accounts and geographic regions. It also provides a framework for coordinating distributed workflows, serverless functions, and contain

    Enables the definition and design of quantum and hybrid algorithms for information processing.

    Pythonawsaws-sdkcloud
    GitHub पर देखें↗9,834
  • dusty-nv/jetson-inferencedusty-nv का अवतार

    dusty-nv/jetson-inference

    8,734GitHub पर देखें↗

    jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti

    Simulates noise events and measurements in Clifford circuits to generate synthetic data for error correction.

    C++caffecomputer-visiondeep-learning
    GitHub पर देखें↗8,734
  • qiskit/qiskitQiskit का अवतार

    Qiskit/qiskit

    7,522GitHub पर देखें↗

    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 hard

    Optimizes and transforms quantum circuit designs to reduce gate counts for hardware execution.

    Pythonpythonqiskitquantum
    GitHub पर देखें↗7,522
  • facebook/redexfacebook का अवतार

    facebook/redex

    6,292GitHub पर देखें↗

    A bytecode optimizer for Android apps

    Runs independent optimization passes in a configurable sequence, each mutating the shared IR.

    C++
    GitHub पर देखें↗6,292
  • nvidia/isaac-gr00tNVIDIA का अवतार

    NVIDIA/Isaac-GR00T

    6,222GitHub पर देखें↗

    Executes quantum computing programs on simulators or quantum hardware using development platforms.

    Jupyter Notebook
    GitHub पर देखें↗6,222
  • quipnetwork/xq-pyQuipNetwork का अवतार

    QuipNetwork/xq-py

    5,546GitHub पर देखें↗

    xq-py एक न्यूमेरिकल क्वांटम कंप्यूटिंग लाइब्रेरी और सॉफ्टवेयर एमुलेटर है जिसका उपयोग क्वांटम एल्गोरिदम को निष्पादित करने के लिए किया जाता है। यह एक क्वांटम वर्चुअल मशीन के रूप में कार्य करता है जो लीनियर अलजेब्रा और कॉम्प्लेक्स नंबर एरेज़ के उपयोग के माध्यम से क्वांटम सर्किट और स्टेट वेक्टर्स का अनुकरण करता है। यह प्रोजेक्ट क्वांटम लॉजिक विकसित करने और सत्यापित करने के लिए एक वर्चुअल वातावरण प्रदान करता है। यह क्वांटम स्टेट वेक्टर्स का अनुकरण करने और संभावित स्टेट कोलैप्स की गणना करने के लिए टेंसर-प्रोडक्ट विस्तार और यूनिटरी गेट अनुप्रयोगों का उपयोग करके मल्टी-क्यूबिट सिस्टम को मॉडल करता है। सिमुलेशन एक न्यूमेरिकल बैकएंड द्वारा समर्थित है जो क्वांटम कंप्यूटेशन एमुलेशन के लिए आवश्यक मैट्रिक्स-आधारित स्टेट ट्रांसफॉर्मेशन और फ्लोटिंग-पॉइंट गणित को हैंडल करता है।

    Provides a virtual environment for developing and verifying quantum logic before physical hardware deployment.

    GitHub पर देखें↗5,546
  • quantumlib/cirqquantumlib का अवतार

    quantumlib/Cirq

    4,990GitHub पर देखें↗

    Cirq, Noisy Intermediate-Scale Quantum (NISQ) हार्डवेयर पर क्वांटम सर्किट को डिज़ाइन करने, सिमुलेट करने और निष्पादित करने के लिए उपयोग किया जाने वाला एक Python क्वांटम कंप्यूटिंग फ्रेमवर्क है। यह एक क्वांटम सर्किट सिम्युलेटर और नॉइज़ मॉडलर के साथ-साथ क्वांटम एल्गोरिदम के कार्यान्वयन के लिए एक टूल के रूप में कार्य करता है। यह फ्रेमवर्क NISQ हार्डवेयर के लिए एक विशेष इंटरफ़ेस प्रदान करता है, जो उपयोगकर्ताओं को हार्डवेयर कनेक्टिविटी और गेट बाधाओं को मान्य करते हुए लॉजिकल क्वांटम सर्किट को फिजिकल डिवाइस टोपोलॉजी पर मैप करने की अनुमति देता है। यह एकीकृत नॉइज़ मॉडलिंग के माध्यम से खुद को अलग करता है, जो वास्तविक क्वांटम प्रोसेसर में पाए जाने वाले डिकोहेरेंस और त्रुटियों की नकल करने के लिए डिपोलराइज़िंग और डैम्पिंग चैनलों को लागू करता है। यह प्रोजेक्ट क्वांटम सर्किट डिज़ाइन, हार्डवेयर एकीकरण और स्टेट सिमुलेशन सहित व्यापक क्षमताओं को कवर करता है। इसमें गेट डिकंपोज़िशन, हार्डवेयर टोपोलॉजी मैपिंग, और फूरियर ट्रांसफॉर्म और असंरचित डेटा खोज जैसी मौलिक क्वांटम प्रक्रियाओं का निष्पादन शामिल है। इसके अतिरिक्त, यह आणविक ग्राउंड स्टेट गणना और हार्डवेयर फिडेलिटी बेंचमार्किंग के लिए विश्लेषणात्मक उपयोगिताएँ प्रदान करता है।

    Provides a comprehensive framework for designing and simulating quantum circuits while accounting for noise and constraints.

    Pythonalgorithmsapicirq
    GitHub पर देखें↗4,990
  • chipsalliance/chiselchipsalliance का अवतार

    chipsalliance/chisel

    4,691GitHub पर देखें↗

    Chisel is a hardware construction language and description tool used to define digital circuits. It functions as a generator that converts high-level hardware descriptions into synthesizable Verilog code for use in ASIC and FPGA design. The project enables the creation of parameterizable hardware templates and reusable digital components. It leverages functional and object-oriented programming patterns to transform complex circuit representations into finalized hardware descriptions. The toolset covers the register-transfer level design workflow, allowing users to model digital circuits usin

    Creates digital electronics and circuit graphs using a high-level programming language.

    Scalachip-generatorchiselchisel3
    GitHub पर देखें↗4,691
  • yosyshq/yosysYosysHQ का अवतार

    YosysHQ/yosys

    4,543GitHub पर देखें↗

    Yosys is a digital logic synthesizer and RTL synthesis tool that transforms hardware description language code into optimized gate-level representations. It functions as a hardware logic optimizer and formal verification tool, providing a framework to convert generic circuit representations into specific technology library cells for targeted hardware platforms. The project serves as a hardware design automator through a scriptable environment used to execute sequences of synthesis commands. This automation allows for the management of complex digital hardware workflows, integrating RTL design

    Employs a modular sequence of optimization passes to iteratively reduce the area and delay of digital circuits.

    C++
    GitHub पर देखें↗4,543
  • ruvnet/ruvectorruvnet का अवतार

    ruvnet/ruvector

    4,253GitHub पर देखें↗

    ruvector is a Rust-based vector store and graph database designed for local inference and nearest neighbor searches. It utilizes a vector graph database architecture and a graph neural network index to refine search rankings through structural attention. The system includes a hardware-accelerated quantum circuit simulator for executing state-vector simulations and complex search patterns, alongside a WebAssembly inference engine for running vector search and model execution directly in web browsers. The project employs a cognitive container format that bundles models, data, and a bootable mic

    Runs state-vector simulations using hardware acceleration to execute complex quantum algorithms and search patterns.

    Rust
    GitHub पर देखें↗4,253
  • microsoft/quantummicrosoft का अवतार

    microsoft/Quantum

    4,043GitHub पर देखें↗

    Quantum is a quantum development framework that provides a hybrid quantum-classical workflow for coordinating execution between classical host languages and quantum processors. It includes a quantum hardware simulator for modeling state evolution and a library of quantum algorithms for tasks such as integer factorization, database search, and quantum arithmetic. The project offers specialized tools for quantum hardware characterization and error correction to manage noise and decoherence. It provides resource estimation modeling to calculate the qubit count and gate depth required to execute

    Enables running quantum circuits on physical hardware or simulators to validate logical operations.

    Jupyter Notebookpythonqdkqsharp
    GitHub पर देखें↗4,043
  • snowkylin/tensorflow-handbooksnowkylin का अवतार

    snowkylin/tensorflow-handbook

    3,927GitHub पर देखें↗

    This project is a comprehensive educational resource and tutorial handbook for building, training, and deploying machine learning models using TensorFlow 2. It serves as a structured learning guide covering core deep learning concepts, including neural network architectures, automatic differentiation, and tensor operations. The handbook provides technical guidance on optimizing execution efficiency through GPU memory management, distributed training, and model quantization. It also includes detailed manuals for constructing high-performance data pipelines and exporting models for production s

    Provides technical details on integrating parameterized quantum circuits as discrete layers for transformations and measurements.

    Jupyter Notebook
    GitHub पर देखें↗3,927
  • atopile/atopileatopile का अवतार

    atopile/atopile

    3,070GitHub पर देखें↗

    atopile is an electronic design automation software and hardware description language that enables the definition of electronic circuits and components as code. It functions as a modular electronics framework and a compiler that transforms programmatic circuit definitions into a normalized model and KiCad project files for physical layout. The system distinguishes itself through automated hardware design automation, using a constraint-based value solver to calculate required component values and validate electrical specifications during the build process. It employs a modular approach to hard

    Models electronics using a declarative hierarchy of modules and components with support for subclassing and inheritance.

    Pythoncadedaelectronics
    GitHub पर देखें↗3,070
  • qiskit/qiskit-tutorialsQiskit का अवतार

    Qiskit/qiskit-tutorials

    2,513GitHub पर देखें↗

    This project is a quantum computing educational resource and implementation library. It provides a collection of interactive notebooks and guides designed for learning quantum programming, developing algorithms, and simulating quantum circuits. The resource includes tutorials for implementing standard quantum algorithms and creating custom circuit passes. It specifically covers quantum hardware control, providing instructions on scheduling raw microwave or laser pulses to implement precise gates at the physical layer. The materials cover the broader surface of quantum circuit design, includi

    Provides an educational environment for learning quantum programming and circuit design.

    Jupyter Notebookqiskitquantum-computingquantum-programming-language
    GitHub पर देखें↗2,513
  • mit-han-lab/torchquantummit-han-lab का अवतार

    mit-han-lab/torchquantum

    1,632GitHub पर देखें↗

    Torchquantum is a tensor-based quantum machine learning library and simulation engine that integrates parameterized quantum circuits directly into PyTorch training pipelines. It enables the construction of hybrid quantum-classical neural networks where quantum operations function as differentiable layers within standard deep learning architectures. The framework computes analytical parameter gradients using native automatic differentiation engines and parameter-shift rules, facilitating end-to-end training and backpropagation. It supports tensor-based quantum state vector simulations, specia

    Simulates quantum computational models and parameterized circuits on classical hardware and accelerators like GPUs for faster execution.

    Jupyter Notebookdeep-learningmachine-learningml-for-systems
    GitHub पर देखें↗1,632
  1. Home
  2. Scientific & Mathematical Computing
  3. High-Performance Execution Environments
  4. Quantum Computing
  5. Quantum Circuit Design

सब-टैग एक्सप्लोर करें

  • AI-Driven Circuit Optimization3 सब-टैग्सUsing generative AI and transformers to design optimized quantum circuits. **Distinct from Quantum Circuit Design:** Specifically uses AI for optimization, distinct from manual or heuristic circuit design.
  • Algorithm Implementation ExamplesReference implementations and step-by-step guides for standard quantum algorithms. **Distinct from Quantum Circuit Design:** Focuses on the provided library of algorithm examples rather than the general design tools.
  • Constraint ValidationsTools for verifying that a quantum circuit adheres to specific device operational rules. **Distinct from Quantum Circuit Design:** A specific analysis capability within the broader quantum circuit design process.
  • Moment-Based ConstructionOrganizing quantum operations into discrete time-sliced moments for scheduling. **Distinct from Quantum Circuit Design:** Focuses specifically on the 'moment' based organizational structure of the circuit.
  • Noise and Measurement EmulationSimulation of noise events and measurements within Clifford circuits. **Distinct from Quantum Circuit Design:** Specifically targets noise and measurement emulation for error correction data, not general circuit design.
  • Parameterizable Hardware GeneratorsTemplates and generators that produce different hardware circuit versions based on input parameters. **Distinct from Quantum Circuit Design:** Focuses on parameterizable generation for general hardware, distinct from quantum-specific circuit design.
  • Quantum Circuit LayeringThe practice of embedding parameterized quantum circuits as discrete layers within neural networks. **Distinct from Quantum Circuit Design:** Distinct from Quantum Circuit Design: focuses on using circuits as functional components of a neural network architecture.
  • Quantum Circuit Transpilation3 सब-टैग्सThe process of transforming abstract quantum circuits into hardware-compatible versions via layout, routing, and optimization. **Distinct from Quantum Circuit Design:** Focuses on the transpilation process specifically, rather than general design or simulation.
  • Quantum Circuit VisualizationRendering quantum circuit diagrams and visual representations of measurement data. **Distinct from Quantum Circuit Design:** Specifically addresses the visual representation of circuits and results, not the design logic.
  • Quantum Outcome SamplingGenerating a distribution of measurement results from a quantum circuit across multiple execution shots. **Distinct from Quantum Circuit Design:** Focuses on the analysis of output samples rather than the design of the circuit itself.
  • Quantum State Preparation2 सब-टैग्सApplying specific gates to qubits to initialize them into desired quantum states. **Distinct from Quantum Circuit Design:** Focuses specifically on the initialization phase of a circuit, whereas design covers the overall structure.
  • Register DefinitionsCreation of qubit sets using abstract names or lattices as targets for operations. **Distinct from Quantum Circuit Design:** A prerequisite step in circuit design specifically focused on qubit allocation.
  • Structure ManipulationsOperations to slice or reverse the sequence of moments within a quantum circuit. **Distinct from Quantum Circuit Design:** Specific structural modification of the circuit's time-sliced organization.
  • Subcircuit NestingEmbedding frozen circuits within other circuits to reduce duplication. **Distinct from Quantum Circuit Design:** Specific capability for reusing circuit blocks, distinct from general design.
  • Tensor Network SimulatorsContracts tensor networks to simulate circuits with many qubits but few gates, reducing memory requirements. **Distinct from Quantum Circuit Design:** Distinct from Quantum Circuit Design: focuses on tensor network contraction for simulation, not general circuit design.
  • Unitary Gate Applications1 सब-टैगThe application of unitary matrices to transform quantum state vectors. **Distinct from Quantum State Preparation:** Covers the general application of any unitary gate during execution, whereas state preparation focuses specifically on initialization.
  • Unitary Matrix Transformations1 सब-टैगLinear algebraic transformations of quantum states using unitary matrices. **Distinct from Quantum State Preparation:** Focuses on the general mathematical transformation process rather than the specific initialization phase of state preparation.