Two characteristics distinguish quantum information technologies from classical information technologies. First, they rely on quantum physics, the sometimes counterintuitive properties of nature at atomic scales. Second, measuring or observing a quantum system fundamentally changes quantum information. These two characteristics cause quantum technologies to process information in a way that is fundamentally different from classical technologies. The difference in processing information begins at the smallest level — a quantum bit, or qubit, which is analogous to a bit in a classical computer.

Quantum computers can, for some problems, dramatically increase processing speed compared to a classical computer. Quantum communications technologies can transmit qubits while maintaining their quantum properties, which is needed to achieve certain security protocols and connect quantum devices. However, they aid each other in certain areas of development.

Introducing the ‘Inspiration series’ by HCLTech Quantum Labs

To understand the scope and progression of the quantum communications market, HCLTech conducted a series of sessions in collaboration with our global innovation partners. The series aims to provide a comprehensive overview of the quantum communications market from academic and industry standpoints, incorporating the business and technology verticals. HCLTech's Quantum Labs, being at the center of innovation, aims to accelerate quantum exploration activities to help industry leaders capitalize on quantum technologies.

The panel in the second episode included Abhinav Khare (Head, Tech Venturing and open innovation ecosystem, CTO Office), Prof. Amlan Chakrabarti (Director, School of IT, University of Calcutta) and Nicolas Robles (Quantum GSI Lead, IBM). The session encompassed rich discussions among the key stakeholders, each bringing their respective viewpoints on paving the way for a quantum secure world.

Safeguarding the communication landscape

We talked about the imminent threat of quantum computers and why there is a need for quantum-safe communication to be set up in our first blog of the series. Robles emphasized that quantum computing would play a key role in protecting data. “IBM has developed an algorithm which protects the information from unethical forms of quantum communication. These algorithms are stronger than RSA and can’t be attacked with quantum computers.”

Quantum Safe Cryptography (QSC) aims to ensure the confidentiality of data by providing encryption methods that are resistant to quantum attacks. This means that even if a quantum computer becomes powerful enough to break traditional encryption, quantum-safe encryption will still protect sensitive information. QSC also addresses the need for secure user identification and authentication. It ensures that only authorized individuals or entities have access to specific resources or information. It focuses on maintaining the integrity of data.

Data cannot be tampered with or altered by unauthorized parties without detection. On the other hand, non-repudiation ensures that the sender of a message or the originator of a transaction cannot deny their involvement. Quantum-safe cryptographic techniques can provide mechanisms for proving the authenticity of digital signatures and the non-repudiation of transactions. Robles stated, “Quantum Safe Cryptography ticks all the boxes regarding confidentiality, identification, integrity and non-repudiation.” Cryptographic systems should continuously evolve because the threat landscape is dynamic. As technology advances, including the potential development of quantum computers, cryptographic algorithms that were once considered secure may become vulnerable.

Quantum computing and communications technology developments are interconnected because they are based on the same quantum physics properties and share common hardware and laboratory techniques. Because of this, it is not always easy to distinguish boundaries between the technologies. Developments in one quantum technology are mutually dependent on developments in another. Qubits being developed will be useful for quantum computing and communications applications such as performing calculations, memory storage or information transmission. For example, in future quantum computers, trapped-ion qubits could be used to perform calculations, with the results converted to photonic qubits for transmission to another qubit technology that would be used as a qubit memory. Each qubit technology has its advantages and challenges that may make it suitable for specific quantum computing or communications applications.

Quantum tech synergy: Unraveling 5G, machine learning and beyond

For all communications to happen securely, there must be encryption between the sender and the receiver. The core of these encryptions are random numbers, sometimes known as cryptographic seeds. Quantum computers can generate quantum numbers that are random and impossible to predict. “To enhance the security, it is advisable to use quantum random numbers, and the randomness would certainly reduce the predictability, making it difficult for hackers to break into the system," said Abhinav. "The problem of pseudo-random numbers is that these are predictable, which raises questions over the security aspect, as these are generated using an algorithm and tend to be biased.” To dig deeper into randomness, one must look at the photonic elements, a proven source of exhibiting randomness. Predicting how photon elements behave when they pass through a splitter is impossible. This may also help in generating keys for quantum key distribution.

It is interesting to understand the intersection of quantum technology, 5G and machine learning and the challenges and opportunities presented by quantum machine learning. The mention of 5G utilizing quantum algorithms suggests that the telecommunications industry is exploring the potential benefits of quantum computing for enhancing network capabilities. Quantum algorithms may be used in various aspects of 5G, such as optimizing network performance, enhancing security and improving signal processing. “Quantum algorithms have the potential to solve complex problems more efficiently than classical algorithms, which can lead to improved network efficiency and data handling,” added Dr. Amlan.

Quantum search algorithms, such as Grover's algorithm, are known for their ability to search unsorted databases or perform optimization tasks more efficiently than their classical counterparts. They can be valuable in optimizing data within 5G networks and help locate optimal network configurations, reduce latency and improve network resource utilization. Quantum machine learning algorithms have the potential to outperform classical machine learning algorithms in specific domains. Still, they also come with unique challenges, such as the need for quantum hardware and error correction.

Connecting multiple quantum computers using quantum networks highlights the concept of distributed quantum computing. This approach involves interconnecting quantum processors to tackle more complex and computationally intensive problems. Quantum networks enable quantum computers to collaborate on tasks that may be beyond the capabilities of a single quantum device. This approach holds promise for solving challenging problems in various fields, including cryptography and optimization. However, it's important to note that this field is still evolving and practical implementations and widespread adoption may take time to materialize.

Applications requiring both quantum technologies

1. Blind Quantum Computing: The concept underlying blind quantum computing revolves around recognizing that, although quantum computers excel exponentially in certain computational tasks compared to classical counterparts, their intricate and costly hardware renders them largely inaccessible to the general populace. Rather than each individual possessing their own quantum computer, blind quantum computing offers a solution by enabling clients to delegate their computing tasks to quantum servers, which execute the tasks on their behalf. It is paramount to ensure that this quantum computation occurs securely and confidentially, particularly given the anticipated security demands of many quantum computing applications.

   Dr. Amlan emphasized the significance of blind quantum computing, characterizing it as a strategy focused on advancing quantum communication at the server level while upholding stringent security measures. As an illustration, financial computations are elevated to the quantum realm, preserving data encryption throughout the transmission process.

2. Distributed Quantum Computing: A distributed quantum computer comprises multiple quantum computer nodes, each equipped with a set of qubits for its computational operations. These quantum computers are interlinked through a network, enabling the exchange of both classical and, notably, quantum bits of information among them. What sets distributed quantum computing apart is the requirement for not only classical network connections to other nodes but also the imperative presence of a quantum network. This quantum network addresses the primary hurdle in distributed quantum computing: executing multi-qubit-controlled operations (such as a CNOT gate) between qubits that are geographically separated on different quantum computers.

What lies ahead?

Quantum computing promises a revolutionary advance in computational power, but applications of quantum mechanics to communication and cryptography may have equally spectacular results and practical implementations may be available much sooner. In addition, quantum communication is likely as essential to quantum computing as networking is to today's computer systems. Most observers expect quantum cryptography to be the first practical application for quantum communications and computing. In the next blogpost, we will dig deeper to understand the implications of the Post Quantum Cryptography (PQC) technique of quantum-safe communication on existing standards.