Sabre Kais Group

Quantum Information and Quantum Computation

Adiabatic Quantum Computing

Adiabatic Quantum Computing

The exact solution of Schrodinger equation for atoms, molecules and extended systems continues to be a "Holy Grail" problem that the entire field has been striving to solve since its inception.

Read More

Quantum Algorithms for Quantum Chemistry

Quantum Algorithms for Quantum Chemistry

Quantum simulation is one of the most promising near term applications for quantum computation that could demonstrate significant advantage over classical algorithms.

Read More

Dimensional Scaling and Finite Size Scaling for Quantum Phase Transitions and Critical Phenomena in atomic and molecular systems

Dimensional Scaling and Finite Size Scaling for Quantum Phase Transitions and Critical Phenomena in atomic and molecular systems

We have established an analogy between symmetry breaking of electronic structure configurations and quantum phase transitions at the large dimensional limit.

Read More

Using Quantum Games to Teach Quantum Mechanics

Using Quantum Games to Teach Quantum Mechanics

The learning of quantum mechanics is contingent upon an understanding of the physical significance of the mathematics that one must perform. Concepts such as normalization, superposition, interference, probability amplitude, and entanglement can prove challenging for the beginning student. Several class activities that use a nonclassical version of tic-tac-toe are described to introduce several topics in an undergraduate quantum mechanics course. Quantum tic-tac-toe is a quantum analogue of classical tic-tac-toe and can be used to demonstrate the use of superposition in movement, qualitative (and later quantitative) displays of entanglement, and state collapse due to observation.

Read More

Entanglement as Measure of Electron-Electron Correlation in Quantum Chemistry Calculations

Entanglement as Measure of Electron-Electron Correlation in Quantum Chemistry Calculations

In quantum chemistry calculations, the correlation energy is defined as the difference between the Hartree–Fock limit energy and the exact solution of the nonrelativistic Schrodinger equation. We have shown that the entanglement can be used as an alternative measure of the electron correlation in quantum chemistry calculations. Entanglement is directly observable and it is one of the most striking properties of quantum mechanics.

Read More

Quantum Computing Using Polar Molecules

Quantum Computing Using Polar Molecules

We investigate several aspects of realizing quantum computation using entangled polar molecules. We develop methods for realizing quantum computation in the gate model, the measurement-based model and the adiabatic model using polar molecules. Moreover, we explore the possibility of a novel quantum computing model built with coupled 2-level systems. The quantum coherent states formed by coupled 2-level systems have unique properties that have inspired numerous ideas in excitonic systems and spin systems.

Read More

Quantum Machine Learning

Quantum Machine Learning

Developing game-changing quantum algorithms to perform machine learning tasks on large-scale scientific datasets for various industrial and technological applications.

Quantum machine learning — a hybridization of classical machine learning techniques with quantum computation – is emerging as a powerful approach both allowing speed-ups and improving classical machine learning algorithms. This program will leverage our expertise in developing quantum algorithms to fully realize the tremendous promise of combining quantum algorithms with machine learning to solve important and challenging problems in quantum chemistry. The first part of the project focuses on combining quantum computing with machine learning techniques for the intent of performing electronic structure calculations. Our initial results for small molecules indicate the feasibility of this combined approach. The second part of the project focuses on developing quantum machine learning techniques for quantum coherence and dynamics for controlling the outcome of chemical reactions. The final part will be On developing hybrid quantum classical machine learning algorithms for data classifications, particularly for quantum phases.

Read More

Book

Quantum Information and Computation for Chemistry (Book)

Edited by Prof. Kais, Chapter 1 (PDF) written by Prof. Kais.