Developing transformative tools at the intersection of quantum computation, AI, and material science.
Building quantum neural networks for financial market prediction and optimization problems.
Computational frameworks for discovering new superconducting materials at scale.
Transformer-based models for quantum chemistry simulations and reaction pathway optimization.
Pioneering initiatives at the forefront of computational science
class QuantumNeuralNetwork {
constructor(qubits = 8, layers = 3) {
this.circuit = new QuantumCircuit(qubits);
this.layers = layers;
this.optimizer = new COBYLAOptimizer();
}
async train(dataset) {
const history = [];
for (let epoch=0; epoch < this.layers; epoch++) {
const result = await this.circuit.run(dataset);
history.push({epoch: epoch, loss: result.getLoss()});
this.optimizer.step();
}
return history;
}
}
This architecture combines variational quantum circuits with classical optimization for financial risk analysis applications.