How to visualize a Quantum Computation. In particular, this article presents a way to understand how superpositions work through a graphical tree.
Category: quantum physics
Some thoughts triggered by the death of the mathematician John Conway.
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Intel engineers have solved the quality control challenge for mass production of quantum computers.
This work provides evidence for something scientists predicted long ago.
Scientists have spotted the first evidence of a rare Higgs boson decay, expanding our understanding of the strange quantum universe.
The toolset runs with Q-CTRL’s flagship BOULDER OPAL software for developers and R&D teams, automated closed-loop hardware optimization is also trained to obtain new experimental data/results from quantum computers while simultaneously running optimizations for algorithms. It can be used as a standalone tool or in tandem with a machine-learner online optimization package (M-LOOP) that manages quantum experiments autonomously.
To build a universal quantum computer from fragile quantum components, effective implementation of quantum error correction (QEC) is an essential requirement and a central challenge. QEC is used in quantum computing, which has the potential to solve scientific problems beyond the scope of supercomputers, to protect quantum information from errors due to various noise.
Over the past few years, many physicists worldwide have conducted research investigating chaos in quantum systems composed of strongly interacting particles, also known as many-body chaos. The study of many-body chaos has broadened the current understanding of quantum thermalization (i.e., the process through which quantum particles reach thermal equilibrium by interacting with one another) and revealed surprising connections between microscopic physics and the dynamics of black holes.
A major skills shortage in quantum computing could harm the UK economy unless universities recruit more students.
Australian scientists have developed a new cryogenic computer system called Gooseberry which has potential for scaling up quantum computers from dozens to thousands of qubits.
The mechanisms that allow the computer to learn are directly embedded in its hardware structure—no extra AI software required.