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Showing posts with label Simulated Annealing. Show all posts
Showing posts with label Simulated Annealing. Show all posts

Friday, July 15, 2022

D-Wave 500 Qubit Quantum Machine on the Cloud

Recall out interaction with D-Wave now dome time ago. often mentioned here. Qubit count is now  impressive.    They continue to advance with their specialty machines.     Would like to see more examples of their applications now.

D-Wave's 500-Qubit Machine Hits the Cloud   By IEEE Spectrum,  July 14, 2022

When quantum-computing pioneer D-Wave releases its next-generation Advantage2 system in 2023 or 2024, the company expects its 7,000-qubit machine to be the most powerful quantum computer of its kind in the world. Now D-Wave is making an experimental prototype of Advantage2 immediately available for use over the cloud.

Classical computers switch transistors either on or off to symbolize data as ones or zeroes. In contrast, quantum computers use quantum bits, or "qubits." Because of the strange nature of quantum physics, qubits can exist in a state called superposition, in which they are essentially both 1 and 0 at the same time. This phenomenon lets each qubit perform two calculations at once. The more qubits are quantum mechanically linked, or entangled, within a quantum computer, the greater its computational power can grow, in an exponential fashion.

The standard approach toward building quantum computers, called the gate model, involves arranging qubits in circuits and making them interact with each other in a fixed sequence. In contrast, D-Wave—based in Burnaby, B.C, Canada—has long focused on what are called annealing quantum computers. Quantum cousins of classical annealing computers, these machines find a lowest energy state by slowly cooling it down—in much the same way that metals and crystals are sometimes tempered so as to minimize imperfections. Quantum annealing machines, then, start off with a set of qubits whose interactions at their lowest energy state, called the ground state, represent the correct answer for a specific problem the researchers programmed it to solve.

From IEEE Spectrum

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Monday, January 10, 2022

Solving Problems with 2D Materials

Note the mention of 'simulated annealing' methods.   

Solving the 'Big Problems' via Algorithms Enhanced by 2D Materials

Penn State News. Jamie Oberdick, January 5, 2022

Pennsylvania State University (Penn State) researchers have developed a method of solving combinatorial optimization problems using two-dimensional (2D) materials. The researchers utilized a simulated annealing algorithm to determine the ground state of an Ising spin glass system. Penn State's Amritanand Sebastian said the process involves conducting in-hardware computational operations, with the hardware deployed via 2D material-based transistors that also store data. "We make use of this in-memory computation capability in order to perform simulated annealing in an efficient manner," he explained. According to Sebastian, the method saves energy through ultra-low-power operation, allows efficient computation of the spin system's energy, and does not require the hardware to scale with the size of the problem.  ... '