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qiskit runtime quantum computing glossary 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 glossary qiskit runtime fundamentals qiskit runtime also called ibm qiskit runtime ibm s cloud execution environment that runs quantum classical workloads near the quantum hardware providing optimized primitives for sampling and expectation value estimation qiskit runtime is ibm s execution model for running quantum programs on ibm quantum hardware rather than sending individual circuits from a user s laptop to the quantum processor and waiting for results qiskit runtime moves the quantum classical computation loop closer to the hardware reducing latency and enabling more efficient execution of iterative algorithms it exposes two core abstractions called primitives sampler and estimator that handle common quantum computation patterns and it supports sessions that maintain dedicated access to a quantum processor across multiple circuit submissions the latency problem variational quantum algorithms like vqe and qaoa follow an iterative pattern run a parameterized quantum circuit measure the results use a classical optimizer to update the circuit parameters repeat without runtime each iteration requires a round trip between the user s machine and the quantum hardware if the quantum processor is in a cloud data center each round trip adds network latency typically 100ms to several seconds for an algorithm requiring thousands of iterations this overhead dominates the total execution time qiskit runtime solves this by executing the entire iterative loop on a classical computer co located with the quantum processor the user submits the full program circuit template optimizer convergence criteria once and the iterative loop runs locally with microsecond scale latency between the classical and quantum components primitives qiskit runtime provides two primitive interfaces that abstract common quantum computation tasks sampler the sampler primitive executes quantum circuits and returns quasi probability distributions over the measurement outcomes it handles circuit transpilation and optimization for the target hardware error mitigation readout error correction twirling batching of multiple circuits for efficient execution returning calibrated probability distributions rather than raw shot counts example use case running a quantum circuit and obtaining the probability of each bitstring outcome estimator the estimator primitive computes expectation values of observables with respect to quantum states prepared by circuits given a circuit ψ θ psi theta rangle ψ θ and an observable o o o it returns ψ θ o ψ θ langle psi theta o psi theta rangle ψ θ o ψ θ the estimator handles decomposing the observable into pauli strings running the necessary measurement circuits one for each non commuting group of pauli terms aggregating results and applying error mitigation returning the expectation value with an error estimate example use case computing the energy expectation value of a molecular hamiltonian in a vqe calculation sessions and execution modes qiskit runtime supports several execution modes job mode submit a single primitive call suitable for one off circuit execution session mode deprecated in favor of batch reserve a quantum processor for a series of related jobs the processor remains allocated between jobs minimizing queuing delays for iterative algorithms batch mode submit a collection of independent jobs that are executed together the system optimizes scheduling across the batch sessions were particularly important for variational algorithms because they ensured that the calibration state of the processor remained consistent across all iterations of the algorithm error mitigation in runtime qiskit runtime integrates several error mitigation techniques twirled readout error extinction trex mitigates measurement errors by randomizing the measurement basis and correcting systematically zero noise extrapolation zne runs circuits at multiple noise levels and extrapolates to the zero noise limit probabilistic error cancellation pec uses a noise model to construct an unbiased estimator of the noiseless expectation value at the cost of increased sampling overhead users select a resilience level 0 through 2 that controls which mitigation techniques are applied trading accuracy for computational cost code example a minimal example using the estimator primitive to compute an expectation value from qiskit circuit import quantumcircuit parameter from qiskit quantum_info import sparsepauliop from qiskit_ibm_runtime import qiskitruntimeservice estimatorv2 connect to ibm quantum service qiskitruntimeservice backend service least_busy operational true build a parameterized circuit theta parameter θ qc quantumcircuit 2 qc h 0 qc cx 0 1 qc ry theta 0 define an observable observable sparsepauliop from_list zz 1 0 xi 0 5 run the estimator estimator estimatorv2 backend bound_circuit qc assign_parameters theta 0 4 job estimator run bound_circuit observable result job result print f expectation value result 0 data evs why it matters for learners qiskit runtime represents the practical software infrastructure needed to run useful quantum algorithms on real hardware understanding runtime is essential for anyone moving beyond textbook quantum circuits to actual quantum computation the primitive abstraction sampler and estimator also reflects a conceptual shift instead of thinking about quantum computing as run a circuit get bitstrings runtime encourages thinking about the computational task sampling a distribution estimating an expectation value and letting the system handle the implementation details including error mitigation see also variational quantum eigensolver qaoa expectation value zero noise extrapolation quantum error mitigation related terms noise model a mathematical description of the errors affecting a quantum processor used in classical simulation to predict how hardware imperfections degrade circuit performance qaoa the quantum approximate optimisation algorithm a variational quantum algorithm for combinatorial optimisation that alternates cost and mixer hamiltonians shot a single execution of a quantum circuit followed by measurement producing one classical bitstring outcome many shots are repeated to estimate probability distributions variational quantum eigensolver a hybrid quantum classical algorithm that uses a quantum computer to estimate the ground state energy of a molecule the leading near term application for quantum chemistry used in these tutorials qiskit runtime sessions and primitives a production guide intermediate 45 minutes qiskit runtime primitives sampler and estimator intermediate 14 min read error suppression with qiskit runtime advanced 35 min advanced error mitigation in qiskit runtime advanced 14 min read 18 tutorials mention this learn more ready to go deeper on qiskit runtime browse structured courses browse courses free tutorials previous qaoa all terms next qma quantum merlin arthur 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 compare frameworks algorithm guide case studies quantum news reference glossary framework docs hardware guide qubit types history timeline cheatsheets bloch sphere quantum programming careers careers guide salary guide certifications interview questions jobs team training post a job talent pool about about this site editorial policy team faq events 2026 podcasts books contact as an amazon associate i earn from qualifying purchases 2026 hadamard llc quantumcomputingcourses com affiliate disclosure privacy terms cookies we use cookies to improve your experience 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