Speaker
Description
The paradigm of quantum computing offers to solve certain computational problems faster compared to the classical computers. However current so called Noisy Intermediate Scale Quantum (NISQ) devices are too noisy to produce results faster or more accurately compared to classical computers. In our research we focus on combining two types of quantum algorithms Variational Quantum Eigensolver (VQE) with Robust Phase Estimation (RPE) to solve time independent Schroedinger equation which can be interpreted as an eigenvalue problem. RPE is a variant of phase estimation algorithm that can correctly returns the eigenvalue as long the eigenstate is known which is not typically true for an eigenvalue problem. Results from the conducted numerical testing show that only the rough estimate of an eigenstate is sufficient input to the RPE in order to produce accurate eigenvalue. To produce the rough estimate of an eigenstate the VQE algorithms was implemented with generic non expressive ansatz, this approach reduces the QPU time and also the size of the parametrized quantum circuit making it more resilient to noise. The most important part of the RPE is an efficient implementation of the controlled unitary operation in the native gate set of given quantum processor since it can produce circuit too large to be efficiently implemented. To prevent creating circuit with thousands two qubit gates the Transitionally Invariant Compressed Controlled (TICC) time evolution was implemented so the created circuits are executable on NISQ devices. This combination of VQE and RPE was implemented to solve the ground state of the Ising model accurately on the noiseless and noisy simulator of the quantum computer. The simulations were conducted using IT4Innovations based supercomputers and models are also prepared to run on the VLQ quantum computer.