What's Annealing Cloud Web ?

Optimization problems exist frequently in everyday life.
When the problem is simple, it can be solved with experience and intuition, but recently the number of complex problems has increased, making it difficult to solve them with the performance of ordinary computers.
As a result, a mathematical approach and dedicated computing technology are required.

The use of annealing machines is left to engineers, but business people are also expected to play a role in problem solving, so the Annealing Cloud Web provides explanations for both.

Basic knowledge of optimization and Annealing Machines

These articles provide an introduction to the basic knowledge
that engineers and business people should have in common.

Towards combinatorial optimization

Towards combinatorial optimization

The processing performance of computers has improved dramatically over time, but it has become clear that optimization problems that meet certain conditions are difficult to solve using conventional computers.
In particular, annealing machines and quantum computers are being considered for efficiently solving combinatorial optimization problems.

Improving society through mathematical technology

Improving society through mathematical technology

Optimization is found all around us. In general, optimization is about determining the best option for you. When there are only a few options to choose from, you can determine a good solution (= combination of variables) using experience and intuition, but as the number of variables to choose from increases, this becomes more difficult. Therefore, we use mathematical approaches and dedicated computing technology (annealing machines) to find a better solution.

For people involved in solving problems

For people involved in solving problems

Although it is engineers who actually use annealing machines, business people are expected to play a role in solving problems. Therefore, Annealing Cloud Web provides explanations not only for engineers but also for business people.

Choose from your roles and Learn

In Annealing Cloud Web, learning content is categorized according to two roles
in order to apply optimization technology to real-world problems.

Engineer

Expert in mathematical approaches and computing technology

Engineer
  • Turning requirements into an optimization problem
  • Choose the right method to get the solution
  • Obtaining optimal solutions with Annealing Machines
Go to ACW Skills Roadmap

Business person (data strategist)

A generalist who promotes problem solving in management and business

Business person (data strategist)
  • Set solutions to achieve their business strategy
  • Clarify the requirements to achieve their own goals
  • Identify the data they need to solve the problem
Go to ACW Skills Roadmap

Learn from the process of solving optimization problems

The project of solving an optimization problem begins with defying business person (a data strategist) who has set a business goal verbalizing the problem.

You can choose to read content based on your own or your team members' perspective or a situation that is close to you.

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Contents

about

ABOUT

In the ”About” section, you can read about an overview of the NEDO project that sponsors this site, information on the technology, and specifications of CMOS annealing from its birth to the current state-of-the-art prototypes, and a collection of links to publications and other resources.


learn

Learn

In the "Learn" section, you will learn about annealing and Ising models, their mathematical background, and their use cases.

Also, a diagnostic tool is available to determine if annealing can help solve your problem.


play

Play

In the "Play" section, you can play with demo applications and Web APIs running on a real CMOS annealing machine (ASIC version). The Ising editor is a visualization of the same loosely coupled Ising model as the real machine, allowing you to see what the process looks like on the Ising model and the numerical output values.
With the free Web API, you can try to solve the problem yourself.