**Dr. Massine Kelai, Center for Quantum Nanoscience **

For those unfamiliar with qubits, we introduce the basics through this series of simple and easy-to-digest graphics. Below, we show the comparison between the bits of a classical computer and the qubits of a quantum computer, and the characteristics of qubits and quantum superposition represented by Schrödinger's cat. In addition, we also introduce the qubit developed here at QNS - the world's smallest qubit and a completely new qubit platform! The representative paper was published in Science on October 2023.

__Episode 1__

In the fascinating field of quantum physics, fundamental units of information, known as quantum bits or qubits, open the door to a new dimension in the understanding and manipulation of information. Unlike the classical bits we use in conventional computers, which can only exist in a binary state of 0 OR 1 at a given moment, qubits can simultaneously occupy states of 0, 1, or even a combination of the two, thanks to a quantum phenomenon known as superposition. This unique property of superposition allows qubits to perform parallel calculations, offering revolutionary potential for quantum computing applications. In addition to superposition, qubits have another essential characteristic called entanglement, which creates a quantum correlation between qubits, even if they are separated by large distances.

A major difference between classical bits and qubits lies in the processing power inherent for the latter case. Whereas classical bits can only represent one state at a time, qubits can exploit the richness of quantum mechanics to process a multitude of information simultaneously, offering revolutionary prospects for solving complex problems and simulating quantum phenomena. These intriguing properties of qubits pave the way for a new era in quantum computing, promising significant advances in fields ranging from cryptography to sensing.

__Episode 2__

In the enigmatic realm of quantum mechanics, Schrödinger's cat paradox serves as a captivating illustration of the perplexing consequences of quantum superposition and wave packet reduction. Coined by physicist Erwin Schrödinger in the 1930s, this intricate thought experiment sheds light on the nuances of particle-wave duality (as explored in the next episode) and pushes the boundaries of our instinctive grasp of the quantum domain. The scenario unfolds in a hypothetical setup featuring a sealed box containing a cat, a vial of poison, a Geiger counter (radiation detector) and a radioactive atom. According to the principles of quantum mechanics, the atom can exist in a superposition state, simultaneously undergoing decay and remaining intact. If the atom decays, the Geiger counter detects the decay, triggering the mechanism that releases the poison into the box, killing the cat. If the atom does not decay, the poison is not released, and the cat stays alive. Consequently, until the atom's state is measured, the cat exists in a superposition, simultaneously alive and dead.

The conceptual challenge intensifies when considering that the observation of the atom's state by an external observer triggers the so-called " the wave packet reduction", compelling the system to adopt a specific state. Thus, the seemingly straightforward act of measuring the quantum system's state appears to dictate a predetermined reality—either dead or alive—defying our conventional understanding of objective reality. This thought-provoking experiment underscores the intricate interplay between observation and quantum reality, presenting a profound challenge to classical intuition. Schrödinger's cat emerges as a fascinating gateway to delving into the mysteries of quantum mechanics and the profound impact of observation on the fundamental nature of reality at the microscopic level.

__Episode 3__

At the heart of the foundations of quantum mechanics lies the fascinating concept of wave-corpuscle duality, an intrinsic characteristic of subatomic particles that defies our classical intuition. Louis de Broglie demonstrated that quantum entities (electrons, photons, neutrons, etc.) can manifest both wave and particle properties, depending on the experimental context. For instance, electrons can interfere like electromagnetic or sound waves (e.g., Young's slit) but can also collide (e.g., Compton effect, photoelectric effect). Given the wave character of quantum particles, they are then described by probability amplitudes with a certain spatial and temporal extensions; this is called the wave function.

Coming back to the Schrödinger's cat paradox (see previous episode), the radioactive atom inside the box and Schrödinger's cat states can be described as a distribution of probability amplitudes. Thus, quantum superposition allows the atom to explore several states simultaneously, opening up the possibility of the cat being both alive and dead until the state is observed. However, the enigma of decoherence comes into play in this context. Quantum decoherence is a process by which the quantum interference between the superposed states of a system is gradually lost as a result of its interaction with the external environment. In the case of Schrödinger's cat, interactions with the outside world, such as air particles or light, can lead to the loss of quantum superposition, forcing the system to adopt a specific state.

To summarize, the complex interplay between the wave and particle aspects of subatomic particles adds a layer of complexity to our understanding of quantum reality, provocatively illustrated by the paradoxical fate of Schrödinger's cat, and decoherence offers a potential explanation for the transition between quantum superposition and a determinate state.

__Episode 4__

At the heart of the coherent qubit manipulation in quantum computing lies the ingenious coherent control of the quantum states by an external stimulus. Unlike conventional bits, which are modified by electrical signals, qubits are sensitive to radio-frequency pulses that can cause them to oscillate coherently between 0 and 1 states, this effect is the so-called Rabi effect. This later constitutes an essential component of operations in today's quantum computers and occurs when an oscillating magnetic field, in the microwave frequency regime, is applied to a set of atoms and molecules and induces transitions between the quantum states of the target object, causing coherent oscillation between these states. This allows a precise coherent control of the quantum state of a qubit by adjusting the frequency and duration of these pulses, opening the way to complex quantum operations. The Rabi effect is not only confined in the physics field, but also played a crucial role in the development of nuclear magnetic resonance spectroscopy (or commonly called MRI, for magnetic resonance imaging), a technique used in a variety of fields in chemistry and medicine.

Quantum logic gates play a fundamental role in carrying out operations on qubits, equivalent to classical logic gates in conventional computers. The Hadamard gate, for example, is crucial for creating superpositions. By applying a Hadamard gate to a qubit initially in the |0⟩ state, we obtain an equal superposition of |0⟩ and |1⟩, paving the way for simultaneous exploration of both states. The CNOT (Controlled-NOT) gate couples two qubits. It acts in such a way as to invert the state of the target qubit (the "NOT") only if the control qubit is in the |1⟩ state. This operation is fundamental to the creation of quantum interleaving and to the implementation of many quantum algorithms.

In summary, the combination of the Rabi effect for controlling qubits by radio frequency and quantum logic gates such as Hadamard and CNOT offers a powerful arsenal for manipulating and processing quantum information. This symbiosis between the precision of quantum control and quantum logic opens up promising horizons for the development of quantum computing, with the potential to solve complex problems exponentially faster than current classical computers.

__Episode 5__

In the intricate realm of quantum computing, the term "Noise Intermediate-Scale Quantum" (NISQ) is emerging as a category of intermediate quantum computers, bridging the gap between prototypes and ambitious large-scale systems. NISQs, composed of a few dozen to a few hundred qubits, are marked by their vulnerability to perturbations, giving rise to quantum errors or 'noise.' These challenges arise due to their sensitivity, and currently, there are generally no extensive quantum error correction capabilities. Despite these obstacles, NISQs offer a promising field for exploration in specific applications, ranging from molecular simulation to optimizing complex problems and quantum machine learning. This pivotal step in the evolution of quantum computing encourages researchers to tackle the challenge of stabilizing qubits and maximizing the potential of NISQs, pushing the frontiers of quantum computation to where classical computers reach their practical limits.

Non-exhaustive examples of quantum computers include:

🔷 Silicon Dopant (Donor Qubits): Donor qubits use individual phosphorus or other dopant atoms in silicon. Notable developments include the Australian Centre for Quantum Computation and Communication Technology's milestones [6] and Silicon Quantum Computing's efforts [7] to develop a full-stack quantum computer using silicon-based qubits.

🔷 Topological Qubits: Microsoft's StationQ project explores topological qubits with semiconductor materials, including silicon [8]. Various global institutions are actively exploring silicon-based donor qubits for quantum computing. Quantum measurement in silicon-based quantum systems often involves techniques like electron spin resonance (ESR), where the qubit's state is probed and read out using the properties of the dopant atoms.

🔷 Trapped Ions: Quantum computers based on trapped ions, serving as qubits, have been studied for years. They are manipulated using laser pulses and specific electromagnetic fields. Quantum measurement of trapped ions is achieved through techniques like laser-induced fluorescence, projecting the quantum state onto one of the ground states, |0⟩ or |1⟩, according to the rules of quantum mechanics. This method provides a controllable quantum system for performing quantum logic gates.

🔷 Superconducting Qubits (Sycamore): Google's top-gate quantum processor, Sycamore, achieved quantum advantage in 2019 with 54 superconducting qubits utilizing transmon qubits coupled to resonators. Quantum measurement often uses the so-called dispersive readout, i.e., a technique involving the readout of the frequency shift of a resonator coupled to the qubit, which depends on the state of the latter. Sycamore completed a task in 200 seconds that would take conventional supercomputers thousands of years. Despite controversies on claiming the quantum advantage, Sycamore signifies significant progress in quantum computing, spurring further research.

🔷 Photonic Quantum Computing (Jiuzhang): Jiuzhang utilizes photon technology, employing "boson sampling" for quantum calculations. Quantum measurement in photon qubits involves photon detectors projecting the photon's state into one of the ground states, |0⟩ or |1⟩, upon measurement. This process generally disturbs the photon's state. Jiuzhang demonstrated manipulating 76 photons, claiming a quantum advantage. However, debates surround its achievement, with critics questioning its generic applicability. Unlike versatile systems like Google's quantum computer, Jiuzhang's limitation lies in performing a specific task.

To conclude this series on a broader note, the advent of quantum computers will revolutionize the world economy by accelerating complex calculations and solving previously insoluble problems, stimulating innovation in finance, logistics, and pharmaceutical research. The transition to this technology requires massive investment [9], and its integration into our economies is a major sustainability issue for nations, offering a significant competitive advantage for businesses.

_{ References
[1]: Wang, Y., et al. Science 382, 87–92 (2023).
[2]: Veldhorst, M., et al. Nature 526, 410–414 (2015).
[3]: (a) https://ionq.com/quantum-systems/forte ; (b) Chen, J-S., et al. arXiv:2308.05071 (2023).
[4]: Arute, F., et al. Nature 574, 505–510 (2019).
[5]: Zhong, H-S., et al. Science 370, 1460-1463 (2020).
[6]: Australian Centre for Quantum Computation and Communication Technology: https://www.cqc2t.org/
[7]: Silicon Quantum Computing: https://sqc.com.au/
[8]: Microsoft's StationQ: https://news.microsoft.com/stories/stationq/
[9]: https://www.bcg.com/publications/2023/enterprise-grade-quantum-computing-almost-ready }