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pennylane documentation pennylane 0 45 1 documentation why pennylane about pennylane features discover easy to use pennylane features to empower your work performance scale up your workflows on gpus and supercomputers to accelerate simulations hardware and simulators explore pennylane s quantum device ecosystem with 40 integrated options use cases applications research accelerate your quantum computing research breakthroughs with pennylane teach join quantum educators in over 150 universities using pennylane in the classroom learn delve into quantum computing quantum chemistry and quantum machine learning featured research use the world s largest quantum demo library to publish breakthrough research research with pennylane teach elevate your curriculum using industry standard tools that build job ready skills explore educator resources documentation documentation install pennylane documentation catalyst documentation development guide how to guides api github getting started latest release pennylane fundamentals begin with a crash course on the basics of pennylane for quantum practitioners get started documentation explore our quantum software api references and development guides view documentation resources quantum computing resources browse all codebook learn quantum computing with pennylane coding challenges test your skills with quantum coding challenges and earn badges videos sit back and explore our curated selection of expert videos demos library explore the quantum landscape with our research level demos written by experts compilation hub find explanations and implementations of important quantum compilation techniques quantum datasets speed up research with quantum datasets tailored for use with pennylane latest quantum computing demos explore demos library topic guides quantum computing topic guides from pennylane fault tolerant quantum computing master the latest advancements in error correcting codes and ftqc hamiltonian simulation discover hamiltonian simulation algorithms from basic to advanced techniques quantum compilation new explore the definitive pennylane guide to quantum compilation techniques quantum gradients access a curated guide of the different quantum gradient methods quantum hardware view how the modalities stack up in the global race to build a scalable quantum computer quantum machine learning learn the different flavours of quantum machine learning in this curated guide featured pennylane topic guides fault tolerant quantum computing master the latest advancements in error correcting codes and ftqc demystify ftqc new quantum compilation explore the definitive pennylane guide to quantum compilation techniques explore quantum compilation community support new community support pennylane blog faqs discussion forum submit a demo get involved from xanadu xanadu blog xanadu press and news latest blog post view all help support pennylane newsletter join the pennylane discussion forum get expert help and connect with the global pennylane community go to forum new pennylane newsletter want to get the latest quantum updates delivered to your inbox join the list subscribe now install why pennylane about pennylane features discover easy to use pennylane features to empower your work performance scale up your workflows on gpus and supercomputers to accelerate simulations hardware and simulators explore pennylane s quantum device ecosystem with 40 integrated options use cases applications research accelerate your quantum computing research breakthroughs with pennylane teach join quantum educators in over 150 universities using pennylane in the classroom learn delve into quantum computing quantum chemistry and quantum machine learning featured research use the world s largest quantum demo library to publish breakthrough research research with pennylane teach elevate your curriculum using industry standard tools that build job ready skills explore educator resources documentation documentation install pennylane documentation catalyst documentation development guide how to guides api github getting started pennylane fundamentals begin with a crash course on the basics of pennylane for quantum practitioners get started documentation explore our quantum software api references and development guides view documentation latest release resources quantum computing resources browse all codebook learn quantum computing with pennylane coding challenges test your skills with quantum coding challenges and earn badges videos sit back and explore our curated selection of expert videos demos library explore the quantum landscape with our research level demos written by experts compilation hub find explanations and implementations of important quantum compilation techniques quantum datasets speed up research with quantum datasets tailored for use with pennylane latest quantum computing demos explore demos library topic guides quantum computing topic guides from pennylane fault tolerant quantum computing master the latest advancements in error correcting codes and ftqc hamiltonian simulation discover hamiltonian simulation algorithms from basic to advanced techniques quantum compilation new explore the definitive pennylane guide to quantum compilation techniques quantum gradients access a curated guide of the different quantum gradient methods quantum hardware view how the modalities stack up in the global race to build a scalable quantum computer quantum machine learning learn the different flavours of quantum machine learning in this curated guide featured pennylane topic guides fault tolerant quantum computing master the latest advancements in error correcting codes and ftqc demystify ftqc new quantum compilation explore the definitive pennylane guide to quantum compilation techniques explore quantum compilation community support new community support pennylane blog faqs discussion forum submit a demo get involved from xanadu xanadu blog xanadu press and news latest blog post view all help support join the pennylane discussion forum get expert help and connect with the global pennylane community go to forum pennylane newsletter new pennylane newsletter want to get the latest quantum updates delivered to your inbox join the list subscribe now install navigation index modules next pennylane 0 45 1 documentation pennylane documentation table of contents search using pennylane what is pennylane quantum circuits gradients and training quantum operators measurements dynamic quantum circuits templates inspecting circuits compiling circuits compiling workflows importing workflows quantum chemistry quantum datasets logging release news release notes deprecations updated operators program capture sharp bits development development guide building a plugin adding new operators api qp qp bose qp compiler qp data qp decomposition qp debugging qp drawer qp estimator qp fermi qp fourier qp gradients qp io qp kernels qp labs qp liealg qp logging qp math qp noise qp numpy qp ops op_math qp pauli qp pulse qp qaoa qp qchem qp qcut qp qnn qp resource qp shadows qp spin qp transforms internals qp capture qp concurrency qp devices qp exceptions qp ftqc qp gate_sets qp measurements qp pytrees qp operation qp queuing qp tape qp templates core qp wires qp workflow docs pennylane documentation pennylane documentation release 0 45 1 pennylane is a cross platform python library for quantum computing quantum machine learning and quantum chemistry train a quantum computer the same way as a neural network using pennylane a guided tour of the core features of pennylane developing how you can contribute to the development of pennylane api explore the pennylane api features follow the gradient built in automatic differentiation of quantum circuits best of both worlds support for hybrid quantum and classical models connect quantum hardware with pytorch jax and numpy just in time compilation compile your entire hybrid workflow with support for adaptive circuits real time measurement feedback unbounded loops and more see catalyst for more details batteries included provides optimization and machine learning tools device independent the same quantum circuit model can be run on different backends install plugins to access even more devices including strawberry fields amazon braket ibm q google cirq rigetti forest microsoft qdk and projectq getting started for an introduction to quantum machine learning we have several guides and resources available on our qml website including what is qml frequently asked questions a glossary of key concepts and a curated selection of qml videos then take a deeper dive into quantum machine learning by exploring cutting edge algorithms using pennylane and near term quantum hardware with our collection of qml demonstrations you can also check out the using pennylane section for more details on the quantum operations and to explore the available optimization tools provided by pennylane we also have a detailed guide on how to write your own pennylane compatible quantum device finally play around with the numerous devices and plugins available for running your hybrid optimizations these include ibm q provided by the pennylane qiskit plugin as well as the rigetti aspen qpu provided by pennylane rigetti how to cite if you are doing research using pennylane please cite ville bergholm et al pennylane automatic differentiation of hybrid quantum classical computations 2018 arxiv 1811 04968 support and contribution source code https github com pennylaneai pennylane issue tracker https github com pennylaneai pennylane issues if you are having issues please let us know by posting the issue on our github issue tracker we encourage contributions simply fork the pennylane repository and then make a pull request containing your contribution all contributors to pennylane will be listed as authors on the releases to chat directly with the team designing and building pennylane as well as members of our community ranging from quantum machine learning researchers to students to those just interested in being a part of a rapidly growing industry you can join our discussion forum license pennylane is free and open source released under the apache license version 2 0 index download python script download notebook view on github next navigation index modules next pennylane 0 45 1 documentation pennylane documentation never miss a milestone get the latest quantum updates delivered to your inbox join the list pennylane is an open source quantum software platform for quantum computing quantum machine learning and quantum chemistry create meaningful quantum algorithms from inspiration to implementation created with ️ by xanadu research research performance hardware and simulators demos library compilation hub quantum datasets education teach learn codebook coding challenges videos glossary software install features pennylane documentation catalyst documentation development guide how to 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