## `eigenkit.core.solver`

The base class every quantum solver inherits.

It lives in `core` rather than in `algorithms` because the four solvers that inherit it sit in three different packages, and `optimization` and `chemistry` depend on `core` alone. In `algorithms`, inheriting it would make those two packages depend on `algorithms`, which they otherwise never touch.

### `BaseQuantumSolver`

Bases: `ABC`

Base class for quantum solvers that compute a result in a single call.

Unlike BaseQuantumEstimator, a solver has no training phase and no fitted state, and it does not follow the scikit-learn estimator interface. It receives a mathematical problem directly in `solve()` and returns a structured result object.

Four classes inherit from it: HHL, IQAE, QAOA and VQE. PortfolioRiskEstimator does not, by design. It is a scikit-learn-style estimator with `fit()`, `estimate()` and `var_at()`, and it has no `solve()` method. As a result, `isinstance(x, BaseQuantumSolver)` tells you whether an object can be given a problem directly, and it returns `False` for the estimator.

Each subclass sets its own `provider` default in its signature and passes it to this class. All of them use `"numpy"`. Two of the modes of `IQAE`, a callable oracle and `shot_mode="provider"`, need `provider="pennylane"`.

Parameters:

| Name       | Type           | Description                                                                                                                                                                                                   | Default   |
| ---------- | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- |
| `provider` | `ProviderSpec` | The backend to use: a registered name ("numpy", "pennylane", "qiskit" and so on), a config instance, or a backend object. The default is "numpy", the built-in simulator that the core installation includes. | `'numpy'` |

Example

```python
from eigenkit.core import BaseQuantumSolver
from eigenkit.optimization import QAOA

isinstance(QAOA(), BaseQuantumSolver)   # True
```

#### `solve(*args, **kwargs)`

Compute and return the solution.

Each subclass declares the signature that its problem needs. `HHL` takes a matrix and a right-hand side, `IQAE` takes an oracle, `QAOA` takes a problem, and `VQE` takes a Hamiltonian and the number of qubits.