Cold Ion Group @ CQT

Introduction

Our work is based on various aspects of ion trap physics and its application. It can be broadly classified as per the current projects into (1) Full stack quantum system development, (2) Reduction of errors in ion trap based quantum processors, (3) Application of quantum algorithms and seeking possible advantages.

A full stack quantum computer development involves develop the sub-systems and integrating into a full system. We are currently leading the National Quantum Processor Initiative for Trapped Ions (NQPI-TI) program. In this program, a room temperature ion trap system that is compatible to existing high performance computing center infrastructure is currently in progress. We started this 20 MSGD program in April 2025.

The novelty of our program is a segmented design capable to implement QCCD path to scaling. The trap is designed to hold dual species Ba and Yb. Most of the sub-systems has been developed in our research laboratories at CQT/NUS. These include: trap design and fabrication, optical sub-systems, RF electronics and middleware as well as the software stack.

One of the set-ups where one can see the segmented trap inside the vacuum chamber at below 10^-10 mbar pressure. This can hold more than 50 ions in a linear chain.

Reduction of error in an ion trap system involves careful measurement, design of sub-systems and fabrication to the best possible precision. We systems are based on Barium optical and hyperfine qubits/qudits. One of the most challenging sub-system for optical qubit is the laser frequency, phase and amplitude stabilization. The team pursues different techniques to minimize the phase and amplitude noise (some of them are presented at the APS March 2026).

To scale the ion trap quantum processors, it is important to develop fast gates without compromising the uniqueness of high fidelity of these gates. We focus on developing novel techniques to improve of gate times as well as their fidelities.

Top row represents experimental results of classification of data using different boundaries by implementing quantum data re-up-laoding algorithm on our quantum system.

Application of quantum algorithms to understand the limits of the current NISQ systems is a strong focus of the group. Seeking quantum advantage means looking for signatures where quantum computers may perform better than classical counterparts. Among the well known algorithms, Shor's algorithm is known to provide super-polynomial speedup in computing prime factors a large number. However, implementing this algorithm in a quantum computer is challenging. It will require millions of qubits which are error corrected to factorize any number that can be of significance to modern day encryption systems. In our group, we seek other possible avenues where quantum advantage may show up. These include accuracy of data classification, energy cost of computation and robustness of training.