Class QuantumLoss<T>

Namespace

AiDotNet.LossFunctions

Assembly

AiDotNet.dll

Represents a quantum-specific loss function for quantum neural networks.

public class QuantumLoss<T> : LossFunctionBase<T>, ILossFunction<T>

Type Parameters

T

The numeric type used for calculations.

Inheritance

object

LossFunctionBase<T>

QuantumLoss<T>

Implements

ILossFunction<T>

Inherited Members

LossFunctionBase<T>.NumOps

LossFunctionBase<T>.Engine

LossFunctionBase<T>.CalculateLossAndGradientGpu(IGpuTensor<T>, IGpuTensor<T>)

LossFunctionBase<T>.ValidateVectorLengths(Vector<T>, Vector<T>)

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Extension Methods

LossFunctionExtensions.ComputeGradient<T>(ILossFunction<T>, Tensor<T>, Tensor<T>)

LossFunctionExtensions.ComputeLoss<T>(ILossFunction<T>, Tensor<T>, Tensor<T>)

Constructors

QuantumLoss()

public QuantumLoss()

Methods

CalculateDerivative(Vector<T>, Vector<T>)

Calculates the derivative of the quantum loss function.

public override Vector<T> CalculateDerivative(Vector<T> predicted, Vector<T> expected)

Parameters

predicted Vector<T>

The predicted quantum state.

expected Vector<T>

The expected quantum state.

Returns

Vector<T>

The gradient of the loss with respect to the predicted values.

CalculateLoss(Vector<T>, Vector<T>)

Calculates the quantum loss between predicted and expected quantum states.

public override T CalculateLoss(Vector<T> predicted, Vector<T> expected)

Parameters

predicted Vector<T>

The predicted quantum state.

expected Vector<T>

The expected quantum state.

Returns

T

The calculated quantum loss.

Remarks

This method implements a form of quantum fidelity loss, which measures how close the predicted quantum state is to the expected quantum state.