What Happened with Quantum Computing
According to Tracxn, there are 41 quantum computing startups, and according to CrunchBase, there are a total of 238 startups operating for quantum computing. The number remains nuanced. The global market of quantum computing is around $35.5 billion. In February, the Indian government announced its plans of investing $1 billion for the next five years towards the development of quantum technology. Quantum technology still remains in a nascent stage globally. Only a handful of big tech companies and a few research institutions in the US, China, and Europe are able to make developments in the sector as the technology requires expertise and high-computing capabilities, not available for everyone. Let’s look at some of the developments in the quantum computing and technology space that took place in 2022. IBM Qubit and z16 IBM is developing a 4000+ qubit quantum computer slated to be completed by 2025. In December, IBM unveiled the world’s first quantum computer with 1,000 qubit, Condor, which is set to debut in 2023. Big Blue is making great strides in the quantum computing field after launching its modular quantum processor, called Heron. In April, IBM released industry’s first quantum-safe system, IBM z16 with an integrated on-chip AI accelerator for delivering low-latency inference for real-time transactions and making history in the quantum security arena. The system leverages IBM’s AI inferencing Telum Processor for high-volume processing. NVIDIA QODA In July, NVIDIA, in a bid to replicate the success of its computing platform CUDA, announced the release of its unified computing platform QODA (Quantum Optimised Device Architecture) for accelerating research in quantum computing across areas like AI, HPC, finance, and health. QODA enables developers to add quantum computing capabilities to their existing applications and thus aims to make the field more accessible by creating a coherent hybrid quantum-classical programming model. The team said that HPC and AI experts can leverage these quantum processors using their DGX systems to simulate the future of quantum computing. India-Finland In March, India and Finland laid out a detailed plan for setting up an Indo-Finnish Virtual Network Centre for quantum computing and identified three institutes – IIT Madras, IISER Pune, and C-DAC Pune for the project. FIN-Q n (Finland India Quantum Network) is built for creating a sandbox environment for both the countries’ companies for quantum technology. TechMahindra has been trying to solidify India’s quantum computing field and now they have signed an MoU with Finnish quantum computing company IQM for advancing the field. The partnership also includes collaborations with Mahindra University for research in quantum computing and explainable AI. Quantinuum Quantinuum announced InQuanto 2.0 for computational chemistry using quantum computing. The new version of InQuanto introduces new tools for greater efficiency, advanced algorithms for speeding up vector calculations and integral operator classes. The tool is now also user-friendly and has improved resource cost estimation on H-series quantum computers. IN-SPACe and QNu Labs Indian National Space Promotion and Authorisation Centre (IN-SPACe) signed an MoU with Bangalore-based QNu Labs for creating domestic satellite QKD (quantum key distribution) products. This will be achieved through the startups increasing use of quantum cryptography for addressing cybersecurity challenges with the classical computing world. The partnership will provide QNu Labs with payload designs with the help of ISRO as well. TCS, Infosys, and AWS In November, TCS made its quantum computing lab available on AWS for enterprise customers for quantum computing and applications. The research and development will be powered by Amazon’s Braket, a fully-managed service offered by AWS for quantum computing. TCS has been collaborating with the government for academic, research, and startups for developing quantum technology. Infosys made big bets and launched Quantum Living Labs for their customers who want to apply quantum computing in their applications like manufacturing, cyber security, healthcare, etc. Twist Programming Language In January, scientists at MIT’s Computer Science and Artificial Intelligence (CSAIL) developed a programming language for quantum computing called Twist. The language relies on the concept of purity for building intuitive programs by enforcing the absence of entanglement, thus resulting in fewer bugs. When programming quantum computers, two qubits are entangled, which results in actions taken on one qubit to affect the other one, resulting in weakness and incorrectness in the program. Twist enables developers to write quantum programs explicitly when a qubit is not entangled with another. Google’s Quantum Virtual Machine In July, Google made another of their products publicly available. Quantum Virtual Machine (QVM) is a tool for prototyping, testing, and optimising quantum circuits with processor-like output for near-term quantum hardware that can now be deployed from Colab notebook. Users can emulate two of its processors – Rainbow and Weber. Weber is a Sycamore processor used in Google’s beyond-classical experiments, published in Nature in 2019. Rainbow is used by the company’s experiments demonstrating variational quantum eigensolver with quantum chemistry problems. SpinQ Triangulum China’s SpinQ published their paper in February about Triangulum, a second-generation, three-qubit desktop quantum computer. In November, they released three portable quantum computers – Gemini, Gemini Mini, and Triangulum – that would be used for educational purposes. These computers use nuclear magnetic resonance (NMR) for performing quantum computations using motion of spins of atoms.
Let’s look at some of the developments in the nascent quantum computing space
Quantum technology still remains in a nascent stage globally. Only a handful of big tech companies and a few research institutions in the US, China, and Europe are able to make developments in the sector as the technology requires expertise and high-computing capabilities, not available for everyone. 
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Mohit writes about AI in simple, explainable, and often funny words. He's especially passionate about chatting with those building AI for Bharat, with the occasional detour into AGI.