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tket reference dictionary skip to main content quantumcomputing courses com courses all courses course platforms coursera edx udemy brilliant hardware providers google quantum ai ibm quantum ionq quantinuum amazon braket azure quantum quera rigetti d wave tutorials all tutorials hello world qiskit hello world cirq hello world pennylane hello world braket quantum gates grover s algorithm shor s algorithm reference all frameworks qiskit cirq pennylane amazon braket pyquil tket d wave ocean q explore learn learning paths prerequisites programming guide case studies glossary books quantum news podcasts tools bloch sphere quantum pinball guides algorithm guide hardware guide qubit types framework comparison migration guide language timeline cheat sheets career events 2026 jobs careers certifications salary guide universities interview prep faq troubleshooting about about team search browse courses home reference tket framework reference tket quantinuum s high performance quantum compiler and sdk python version 2 x 10 sections quick reference for pytket circuits gates compiler passes backends and running on quantinuum hardware in this guide 10 sections 01 background and history 02 installation 03 key imports 04 circuit construction 05 gates 06 measurement 07 compiler passes 08 backends 09 tket vs qiskit s transpiler 10 common patterns at a glance language python version 2 x install pip install pytket copy docs docs quantinuum com source quantinuum tket background and history tket pronounced ticket is a quantum compiler and circuit optimization toolkit originally developed by cambridge quantum computing cqc a uk based quantum software company founded in 2014 by ilyas khan cqc began developing tket around 2018 as an advanced circuit compilation engine focused on reducing two qubit gate counts which are the primary source of error on near term quantum hardware the python interface pytket was released to provide accessible programmatic access to tket s compilation passes in june 2021 cambridge quantum computing merged with honeywell quantum solutions which operated trapped ion quantum processors to form quantinuum this merger placed tket under the same corporate umbrella as the h series trapped ion hardware making it the native compiler for quantinuum s processors the tket source code was open sourced in late 2021 under the apache 2 0 license making the full compiler stack available for community inspection and contribution tket s core strength is its compiler pass infrastructure passes such as fullpeepholeoptimise cliffordsimp and synthesisetket apply local rewriting rules and resynthesis techniques to minimize circuit depth and gate count these optimizations are hardware aware when targeting a specific backend tket respects the device s connectivity constraints and native gate set while optimizing independent benchmarks have shown tket producing competitive or superior two qubit gate counts compared to other compilers across multiple hardware platforms a distinctive feature of tket is its cross platform backend system through extension packages pytket qiskit pytket cirq pytket braket pytket quantinuum and others tket can accept circuits from most major frameworks and compile them for most major hardware targets this makes it useful as a universal optimization layer regardless of which frontend or backend a team prefers as of 2026 pytket is actively maintained by quantinuum with regular releases on the 2 x series it has a dedicated user community particularly among researchers who need aggressive circuit optimization for near term experiments and among quantinuum hardware users installation pip install pytket backend extensions one per target pip install pytket qiskit ibm aer pip install pytket cirq google cirq pip install pytket quantinuum quantinuum compilation and local emulation pip install pytket braket amazon braket pip install qnexus job submission to quantinuum hardware nexus platform key imports from pytket import circuit optype from pytket extensions qiskit import aerbackend from pytket passes import fullpeepholeoptimise decomposeboxes circuit construction from pytket import circuit circ circuit 2 2 2 qubits 2 classical bits circ circuit 3 3 qubits no classical bits qubits and bits are indexed from 0 circ h 0 hadamard on qubit 0 circ cx 0 1 cnot control 0 target 1 circ measure_all measure all qubits into matching classical bits gates circ h q hadamard circ x q pauli x circ y q pauli y circ z q pauli z circ s q s gate circ sdg q s dagger inverse s circ t q t gate circ tdg q t dagger inverse t circ cx control target cnot circ cz q1 q2 controlled z circ swap q1 q2 swap circ ccx q1 q2 q3 toffoli rotation gates angles in half turns 1 0 π radians circ rx 0 5 q rx π 2 circ ry 0 5 q ry π 2 circ rz 0 5 q rz π 2 parameterised gates for variational algorithms from pytket circuit import fresh_symbol theta fresh_symbol theta circ ry theta 0 tket uses half turns a rotation of 1 0 π radians so rx 0 5 rx π 2 multiply standard radian values by 1 π measurement circ measure_all measure all qubits circ measure qubit classical_bit measure specific qubit measure a whole qubitregister into a named classical register qreg circ get_q_register q default qubit register circ measure_register qreg m compiler passes tket s main value is its compiler passes reduce gate count and adapt circuits to backend constraints from pytket passes import fullpeepholeoptimise synthesisetket cliffordsimp removeredundancies sequencepass apply a single pass fullpeepholeoptimise apply circ chain passes sequencepass removeredundancies fullpeepholeoptimise apply circ common passes pass what it does removeredundancies cancels adjacent inverse gates cliffordsimp optimises clifford sub circuits fullpeepholeoptimise heavy local rewriting for 2 qubit count synthesisetket full circuit resynthesis decomposeboxes unfolds boxed sub circuits backends aer simulator via pytket qiskit from pytket extensions qiskit import aerbackend backend aerbackend compile the circuit for the backend first compiled backend get_compiled_circuit circ handle backend process_circuit compiled n_shots 1024 result backend get_result handle print result get_counts print result get_shots raw shot array print result get_probability_distribution dict outcome tuple probability statevector simulation from pytket extensions qiskit import aerstatebackend backend aerstatebackend state backend run_circuit circ get_state quantinuum hardware since pytket quantinuum 0 56 the extension handles compilation and local emulation only the old quantinuumbackend login submission flow no longer reaches hardware jobs are submitted to quantinuum systems through the quantinuum nexus platform using the qnexus package note also that the system model h1 machines such as h1 1 were retired from commercial operation in october 2025 h2 and later systems are the current targets compilation and local emulation pytket quantinuum no cloud account needed install the local emulator with pip install pytket quantinuum pecos from pytket extensions quantinuum import quantinuumbackend backend quantinuumbackend device_name h2 1le local emulator compiled backend get_compiled_circuit circ optimisation_level 2 result backend run_circuit compiled n_shots 100 hardware submission goes through quantinuum nexus import qnexus as qnx qnx login create a project upload the circuit and start compile execute jobs via the qnexus api see https docs quantinuum com nexus for the workflow tket vs qiskit s transpiler both tket and qiskit ship a circuit optimizer and in practice the choice comes down to how locked in a team already is to one ecosystem aspect tket pytket qiskit transpiler scope framework agnostic takes circuits from qiskit cirq or braket via extension packages native to qiskit circuits optimisation approach dedicated passes such as fullpeepholeoptimise and cliffordsimp focused on 2 qubit gate reduction preset optimization_level 0 3 mostly rule based rewriting best fit teams needing aggressive optimization across multiple backends or quantinuum hardware users teams staying entirely within the qiskit ibm stack maintainer quantinuum ibm choose tket when a circuit needs to move between backends or is headed to quantinuum hardware choose qiskit s built in transpiler when the rest of the pipeline circuits backends and primitives is already qiskit native and an extra dependency isn t worth it common patterns bell state from pytket import circuit from pytket extensions qiskit import aerbackend circ circuit 2 2 circ h 0 circ cx 0 1 circ measure_all backend aerbackend compiled backend get_compiled_circuit circ result backend run_circuit compiled n_shots 1024 print result get_counts circuit inspection print circ n_qubits number of qubits print circ n_gates total gate count print circ depth circuit depth print circ n_2qb_gates two qubit gate count main hardware cost print circ get_commands list of all operations symbolic compilation from sympy import symbols pi from pytket import circuit theta symbols theta circ circuit 1 circ ry theta pi 0 tket angles are in half turns circ symbol_substitution theta 1 57 tket tutorials this page is the syntax these are the 8 tutorials where you run it hello world in tket pytket beginner 12 min read advanced circuit optimization with tket advanced 60 minutes circuit optimisation with tket intermediate 12 min read custom compilation passes in tket advanced 35 min all 8 tket tutorials other python frameworks amazon braket aws s fully managed quantum computing service and python sdk amazon braket sdk unified sdk for quantum computing on amazon braket bloqade quera s framework for neutral atom quantum computing and analog hamiltonian simulation cirq google s python framework for quantum circuits and algorithms where to go next the reference index puts tket next to the other 25 frameworks documented here and the comparison page runs the same circuit through each of the major sdks reference index compare frameworks on this page 01 background and history 02 installation 03 key imports 04 circuit construction 05 gates 06 measurement 07 compiler passes 08 backends 09 tket vs qiskit s transpiler 10 common patterns read next all 26 framework dictionaries the full index filterable by language the same circuit in every framework side by side syntax across the major sdks framework tutorials step by step hello world guides for every major quantum sdk get one quantum email a week new tutorials courses worth taking and what changed in qiskit cirq pennylane this week no spam unsubscribe anytime email address subscribe 112 courses 220 tutorials 241 glossary terms 26 framework references 34 case studies quantumcomputing courses com free tutorials curated courses framework references and tools for anyone learning quantum computing written and maintained by dr donovan who writes on quantum computing research hardware and industry at quantum zeitgeist learn all courses free tutorials learning paths 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