Computers are changing swiftly, which has brought us to a new era where the flaws with classical computing are becoming clearer and clearer. Problems are getting so hard that even the most powerful regular supercomputers can't solve them. This is true in fields like cryptography, drug development, materials research, and logistics optimisation. Quantum computing might be a good choice because it can execute a lot of calculations at once using quantum effects like superposition and entanglement. However, modern quantum systems, which are frequently called Noisy Intermediate-Scale Quantum (NISQ) devices, have a lot of issues, like not having enough qubits, having short coherence times, and making a lot of mistakes.Read more...

Quantum computing is moving quickly, but it's still challenging to use in real life since there isn't enough quantum gear and software that can be used in large groups. Cloud-based quantum computing has become a promising way to make quantum workloads more accessible and bigger. This research looks at quantum software frameworks that can be scaled up and work in cloud-based quantum computing systems. It looks at their architectural designs, functional capabilities, techniques for integration, and problems with scaling. We look at major frameworks including IBM's Qiskit, Google's Cirq, Microsoft's Q#, and Amazon Braket in terms of how modular they are, how abstract they are, how flexible their programming is, and how well they operate. Read more...

AI is employed in practically every field, but the rapid growth of AI workloads is making it impossible to stay up with speed, energy utilisation, and the capacity to add more technologies. GPUs and TPUs are two examples of classic hardware accelerators that have gone beyond Moore's Law, although there are still certain basic physical limits. Quantum computers can speed up some operations a lot, but current systems are still constrained by their size and the fact that they lose coherence. But photonics might be a good platform because it can convey messages quickly, doesn't need a lot of power, and works at room temperature. This study looks at Photonic Quantum Neural Networks (PQNNs) as a new technique to speed up AI tasks by using quantum computing theory and photonic hardware together.Read more...

Quantum Secure Multiparty Computation (QMPC) is a new way to use cryptography that lets a lot of people work together to compute a function over their private inputs while keeping those inputs secret, even if attackers have quantum computing power. As AI becomes more common in fields like healthcare, banking, and self-driving cars, secure collaborative learning becomes more and more important. But the rise of quantum computers is a big threat to the encryption methods that are commonly used in modern multiparty computation protocols. QMPC is a very secure and scalable way to protect privacy in AI. It does this by combining quantum-safe oblivious transfer (QOT), quantum key distribution (QKD), and quantum oblivious linear evaluation (qOLE).Read more...

Quantum entanglement is one of the most startling but strong aspects in quantum mechanics. It will be an important feature of communication networks in the future. At its most basic level, entanglement is when two or more quantum particles get linked in such a way that the state of one particle is instantly linked to the state of another, no matter how far apart they are. Einstein dubbed this "spooky action at a distance," and it has made many highly interested in how it could be employed in incredibly quick and safe methods for sending data. As the need for global data rises exponentially, researchers are looking into whether quantum entanglement could be the basis for communication networks that are far faster and safer than traditional ones. Read more...