Release News: July 2026

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A Faster, Scalable Synthesis Architecture

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Exporting to Target Languages

# synthesis preferences: a target gate set and qubit connectivity
synthesis_preferences = Preferences(
    custom_hardware_settings=CustomHardwareSettings(
        basis_gates=["cx", "rz", "sx", "x"],
        connectivity_map=[(0, 1), (1, 2), (2, 3)],
    )
)
qprog = synthesize(main, preferences=synthesis_preferences)

# transpilation_config=True reuses the gate set and connectivity from the synthesis preferences
qasm = export(qprog, target_language=TargetLanguage.QASM3, transpilation_config=True)

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Fault-Tolerant Export

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Circuit Metrics

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Hardware Benchmarking

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Enhancements

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New QLayer Interface for QNN

from classiq import Pauli
from classiq.applications.qnn import QLayerV2

layer = QLayerV2(
    # a synthesized QuantumProgram
    prog,
    # optional observables to estimate; one output feature each (two in this case)
    observables=[Pauli.Z(0), Pauli.X(1) + Pauli.Z(2)],
)

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Language Ergonomics

• New classical functions range_ and reversed_, mirroring Python’s range and reversed, are now available. They operate on Qmod classical variables within classical expressions.
• The subscript and slice_ path operators can now be imported directly from the top-level classiq package (from classiq import *), and no longer need an explicit import.
• Declaring a local quantum variable as a QArray or QNum now requires only its defining arguments, where a name was previously required as well.

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Direct Execution Session Configuration

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Backend Modality Data

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Optional Execution Progress Logging

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Documentation Additions

• Hardware Benchmarking Guide: Covering the new functional-level benchmarking suite, the different predefined benchmarks, how each is scored, and how to run them. For more information, see the Hardware Benchmarking section above.
• QLayerV2 Guide: Covering the streamlined QLayerV2 layer for hybrid QNNs, its interface and observables, worked examples, and how to choose between it and the existing QLayer. For more information, see the New QLayer Interface for QNN section above.

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Library Additions

• Projection-Based Embedding: A notebook demonstrating the Wavefunction-in-DFT Embedding capability added in June, putting the EmbeddingCalculator to use on a water molecule. It treats a chemically active fragment with a quantum method such as VQE while describing the surrounding environment with DFT, then recombines the two to recover the total energy.
• Numerical Gradient Estimation: Implementing Jordan’s algorithm to estimate the gradient of a d-dimensional scalar function with a single quantum query, in place of the d+1 evaluations a classical finite-difference approach would require.
• Quantum Likelihood Estimation: A hybrid algorithm for Hamiltonian learning that identifies an unknown Hamiltonian, accessible only through the time evolution it generates, from a candidate set. It implements the optimal variant, developed with the paper’s authors, which jointly optimizes all five circuit parameters each iteration to make every measurement maximally informative. It converges in roughly an order of magnitude fewer experiments than standard QLE.

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Bug Fixes

• Synthesis now catches unsafe qubit-layout changes in control-flow blocks: reordering a quantum variable’s qubits inside a power, repeat, foreach, or if block is now rejected up front with a descriptive error.
• Classical path operators return correctly-typed results: subscript, slice_, and reversed_ in the Python SDK now correctly infer their result type from their argument.
• observe no longer emits a spurious deprecation warning: calling the observe function now runs cleanly, after previously surfacing a misplaced submit_estimate() is deprecated warning.
• Quantum variable constructors reject non-string names cleanly: passing a non-string name to QArray, QNum, QBit, or QStruct now raises a clear error, where it previously failed internally.

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Deprecations

• QuantumProgram.qasm and transpiled_circuit deprecated: following the synthesis architecture update, these QuantumProgram attributes are replaced by export for a QASM circuit and get_circuit_metrics or get_transpiled_circuit_metrics for resource estimation, as covered in the synthesis architecture section above.
• execute_qnn accepted observable type change: execute_qnn now takes its observable as a SparsePauliOp; passing the deprecated PauliOperator is converted automatically, and emits a DeprecationWarning.
• slice Qmod operator renamed to slice_: calling slice now emits a deprecation warning; use slice_ instead.