> ## Documentation Index
> Fetch the complete documentation index at: https://prod-mint.classiq.io/llms.txt
> Use this file to discover all available pages before exploring further.

# 1.8.0

Released on 2026-03-30.

## Upgrade Instructions

* [Python SDK](../getting-started/registration_installations.md/#platform-version-updates)
* The IDE upgrades automatically.

## Enhancements

* **`sample` function:** Added a new top-level `sample` function for executing a quantum program and retrieving results as a DataFrame directly, without managing a job object. Supports single and batch execution — pass a list of parameter dictionaries to `parameters` to run multiple parameter sets and receive a list of DataFrames. Also supports `run_via_classiq=True` to run using Classiq's provider credentials against your allocated budget. See the [SDK reference](../sdk-reference/execution/) for details.
* **`observe` function:** Added a new public `observe` function that computes the expectation value of a Hermitian observable with respect to a quantum program's output state. Supports exact statevector calculation or shot-based estimation, batch execution, and `run_via_classiq`. See the [SDK reference](../sdk-reference/execution/) for details.
* **`get_backend_details` function:** Added a `get_backend_details` function that returns a DataFrame of all supported quantum backends, including provider, backend name, type (hardware or simulator), qubit count, availability, pending jobs, and queue time.
* **`calculate_state_vector` function:** Added a new public `calculate_state_vector` function that returns the full state vector of a quantum program as a DataFrame. Supports batch execution by passing a list of parameter dictionaries. Available on Classiq simulators (e.g. `classiq/simulator`).
* **`minimize` function:** Added a new public `minimize` function for variational optimization of a cost function over the parameter values of a quantum program. Supports Hamiltonian and classical cost functions, `run_via_classiq`, and improved input validation. See the [SDK reference](../sdk-reference/execution/) for details.
* **OpenQASM in `sample` and `ExecutionSession`:** You can pass **OpenQASM 2.0 or 3.0** source as a string to `sample()` (first argument) or to `ExecutionSession` instead of a synthesized `QuantumProgram`. Results use the same histogram DataFrame shape (`bitstring`, `counts`, etc.). The `parameters` argument is not supported for OpenQASM strings (use a `QuantumProgram` for Qmod `main` parameters, or bind parameters inside the QASM circuit). See the [Execution](../user-guide/execution/#sampling-openqasm) section of the user guide.
* Improve error messages related to qfunc arguments.
* Add `emulate` on `AzureBackendPreferences` to enable IonQ hardware noise simulation on Azure Quantum when using an IonQ QPU target (`ionq.qpu.*`); ignored for other Azure targets.
* Add a QSVM application with a `QSVM` class that provides `train`, `test`, and `predict` methods for easy implementation of Quantum Support Vector Machine training and data classification. The relevant notebooks in the classiq-library will be updated accordingly.