Before quantum computers and quantum networks can fulfil their huge potential, scientists have got several difficult problems to overcome – but a new study outlines a potential solution to one of these problems.
As we’ve seen in recent research, the silicon material that our existing classical computing components are made out of has shown potential for storing quantum bits, too.
These quantum bits – or qubits – are key to next-level quantum computing performance, and they come in a variety of types.
Reimagining Nuclear Medicine — Dr. Stephen Moran, Ph.D., Global Program Head, Neuroendocrine Tumors & Other Radiosensitive Cancers, Advanced Accelerator Applications, Novartis
Dr. Stephen Moran, Ph.D., is Global Program Head, Neuroendocrine Tumors & Other Radiosensitive Cancers, for Advanced Accelerator Applications (AAA — https://www.adacap.com/), a Novartis company and also a member of the Oncology Development Unit Leadership Team at Novartis.
Prior to joining AAA, Dr. Moran was Global Head of Novartis Strategy, where he played a key role in defining the company’s strategy, prioritizing critical actions needed to deliver on the mission to discover new ways to extend and improve peoples’ lives. He also led numerous strategic initiatives, including gene therapy (AveXis, now Novartis Gene Therapies), RNA therapeutics (The Medicines Company), precision medicine and digital strategies.
Dr. Moran joined Novartis as Strategic Assistant to the CEO, a position he held for two years and prior to this, he was an associate principal at McKinsey & Company serving as a leader in the healthcare practice, where he focused on health system sustainability, research and development strategy, and the economic analysis of clinical interventions across disease pathways.
Dr. Moran holds a Bachelor of Arts and a Master of Science in Biochemistry from the University of Cambridge in the United Kingdom, including an undergraduate exchange program at the Massachusetts Institute of Technology (MIT). He also received a Doctorate from the University of Oxford in Biophysics where he lectured on thermodynamics, quantum mechanics and electromagnetism as applied to biology.
Researchers at Simon Fraser University have made a crucial breakthrough in the development of quantum technology.
Their research, published in Nature today, describes their observations of more than 150,000 silicon “T center” photon-spin qubits, an important milestone that unlocks immediate opportunities to construct massively scalable quantum computers and the quantum internet that will connect them.
Quantum computing has enormous potential to provide computing power well beyond the capabilities of today’s supercomputers, which could enable advances in many other fields, including chemistry, materials science, medicine and cybersecurity.
Senior Analyst, AI & Quantum Computing, Paul Smith-Goodson, dives in as in today’s world, many critical business decisions and customer-facing services rely on accurate machine learning insights. Today, he discusses Google’s latest A.I. benchmarking test dethroning NVIDIA’s.
NVIDIA introduces QODA, a new platform for hybrid quantum-classical computing, enabling easy programming of integrated CPU, GPU, and QPU systems.
The past decade has seen quantum computing leap out of academic labs into the mainstream. Efforts to build better quantum computers proliferate at both startups and large companies. And while it is still unclear how far we are away from using quantum advantage on common problems, it is clear that now is the time to build the tools needed to deliver valuable quantum applications.
To start, we need to make progress in our understanding of quantum algorithms. Last year, NVIDIA announced cuQuantum, a software development kit (SDK) for accelerating simulations of quantum computing. Simulating quantum circuits using cuQuantum on GPUs enables algorithms research with performance and scale far beyond what can be achieved on quantum processing units (QPUs) today. This is paving the way for breakthroughs in understanding how to make the most of quantum computers.
In addition to improving quantum algorithms, we also need to use QPUs to their fullest potential alongside classical computing resources: CPUs and GPUs. Today, NVIDIA is announcing the launch ofQuantum Optimized Device Architecture (QODA), a platform for hybrid quantum-classical computing with the mission of enabling this utility.
The potential of quantum computing can in no way be undermined today as it solves some of the most obstinate challenges from bringing down global warming to dramatically bringing down drug discovery time and much more. And with this, several companies are in a spree to bring up quantum computing capabilities.
Nvidia has announced a unified computing platform that will bring in an open environment across quantum processors and classical computers. The company said that the platform aims at speeding enhanced quantum research and development across Artificial Intelligence (AI), High Performance Computing (HPC), health, finance and other disciplines.
The company claims that Nvidia Quantum Optimized Device Architecture or QODA is a first-of-its-kind platform for hybrid quantum-classical computers and aims to make quantum computing more accessible by creating a comprehensive hybrid quantum-classical programming model.
When talking about quantum physics, people will often nonchalantly say that particles can be in two places at once. Physicist Sabine Hossenfelder explores what is actually going on.
