Research conducted by Princeton University physicists is paving the way for the use of silicon-based technologies in quantum computing, especially as quantum bits – the basic units of quantum computers.
Engineers and materials scientists studying superconducting quantum information bits (qubits)—a leading quantum computing material platform based on the frictionless flow of paired electrons—have collected clues hinting at the microscopic sources of qubit information loss. This loss is one of the major obstacles in realizing quantum computers capable of stringing together millions of qubits to run demanding computations. Such large-scale, fault-tolerant systems could simulate complicated molecules for drug development, accelerate the discovery of new materials for clean energy, and perform other tasks that would be impossible or take an impractical amount of time (millions of years) for today’s most powerful supercomputers.
The next generation of computing and information processing lies in the intriguing world of quantum mechanics. Quantum computers are expected to be capable of solving large, extremely complex problems that are beyond the capacity of today’s most powerful supercomputers.
NUST MISIS Scientists Got Photons to Interact, Taking Step Towards Long-Living Quantum Memory An international research team, obtained experimental evidence for effective interaction between microwave
Building a Fault-Tolerant Quantum Computer, The Amazon Way Read More… + Recently, a team from AWS Center for Quantum Computing released its first architecture paper
Qmode project with QuiX QuiX and PHIX started a collaboration in the project Qmode to overcome the packaging challenges of connecting large-scale quantum photonic processors
Recent quantum computing developments have revealed possibilities of stable quantum environments that are ‘reasonable’ in resource requirements. The tool of “sampling complexity” plays into the power of a small quantum computer versus a classical computer. Sampling complexity, the tool, “…involves a mathematical tool—a standard measure of computational difficulty known as sampling complexity—that gauges how easy or hard it is for an ordinary computer to simulate the outcome of a quantum experiment.”
