For example, the quantum circuit model is the most widely used and flexible model, but it requires a lot of qubits and gates to implement complex algorithms. The quantum adiabatic model is more ...

Simon's algorithm consists of two parts - a quantum circuit and a classical post-processing routine which calls the quantum circuit repeatedly and extracts the answer from the results of the runs. In ...

It can be shown that if quantum algorithms run on quantum computers, their processing speeds improve exponentially compared to their classical counterparts. However, due to the lack of quantum ...

Based on a text description, these models ... quantum circuits based on the text description of the quantum operation to be performed. Finding the right quantum gate sequence is necessary to prepare a ...

The topic of this thesis is circuit-based quantum algorithms, which consists of three parts ... Boolean fan-in gates and query gates for quantum memory models. Second, the thesis addresses the optimal ...

These techniques—MPS encoding, genetic algorithms, and variational circuits—offer a unique strategy for efficient quantum state preparation. By minimizing circuit depth and gate count, they aim to ...

Building on a landmark algorithm, researchers propose a way to make a smaller and more noise-tolerant quantum factoring circuit for cryptography ... Fellowship, and a Simons Investigator Award.

The GQE method, however, is the first to leverage AI to accelerate NISQ applications, optimizing parameters classically within the GPT model. GQE extends NISQ algorithms by: Building quantum circuits ...

The authors derived a classical algorithm for simulating random circuit sampling and proved that its runtime is a polynomial function of the time required to run the corresponding quantum experiment.