Today’s Brief Commentary:
Inspired by a discussion with a representative from Toshiba at the Quantum.Tech DC event this week, my links and comments today are related to annealing and optimization. In the quantum space, D-Wave is perhaps the best known with a “quantum annealing” technique, and they have been working on this since their founding in 1999. Annealing itself has a long history, first in metallurgy and then as an optimization technique. D-Wave describes other applications of their offerings on their website.
There are many forms of optimization and applications of it. For example, the traveling salesperson problem is a task for optimization software and, sometimes, specialized hardware. Even if you cannot solve an optimization problem exactly, there are usually heuristics that get fairly close to a good answer. In the context of quantum computing, I discuss optimization in Chapter 12 of my book Dancing with Qubits, Second Edition.
Optimization applications exist in almost every industry, and people who focus on them work in disciplines called operations research, management science, systems analysis, and decision science, to name a few. You often have choices regarding the algorithms, implementations, and hardware you use.
Don’t assume there is only one way to accomplish your goal. For this reason, you might consider an approach using D-Wave, Fujitsu, Toshiba, or one of the classical optimization software packages from IBM, Gurobi, or MathWorks. I provide links below; take these as example starting points.
We must always ask ourselves the following questions when looking for an optimization solution, annealing or otherwise:
- Are we balancing speed, accuracy, computing resources, cost, and energy consumption?
- Can a classical approach do better or sufficiently close to a quantum one today?
- Is any improvement simply linear (for example, 10% faster), or are we seeing quadratic or better?
- Have we thoroughly investigated the range of classical optimization tools?
- Will the proliferation of GPU-laden data centers push the timeline for the necessity of a quantum solution further to the right?
- Where is the cross-over point in the size of the problem between classical and quantum optimization solutions?
- How will our chosen approach scale with the size of the problem?
- Will classical approaches suffice until we get big enough and powerful enough universal quantum computers using a digital or analog paradigm? (D-Wave is working on a digital approach.)
The growth of the quantum computing industry has set up a very healthy and beneficial competition between classical and quantum computing algorithm developers. A “quantum-inspired” algorithm is a classical algorithm created by people who got good ideas from quantum approaches.
They help with SEO because that magical word “quantum” is present. Just add “AI,” as so many do, and you’ll be among the top search results!
Don’t forget to check out and bookmark my new sortable list of upcoming quantum technology conferences.
The latest Sutor Group report is freely available online: Quantum Processing Unit (QPU) Market Landscape (Abridged) – April 3, 2025.
Contents
Classical and “Quantum-Inspired Annealing”
Fujitsu Digital Annealer
https://www.fujitsu.com/global/services/business-services/digital-annealer/
Excerpt: Fujitsu‘s Digital Annealer provides an alternative to quantum computing technology, which is at present both very expensive and difficult to run. Using a digital circuit design inspired by quantum phenomena, the Digital Annealer focuses on rapidly solving complex combinatorial optimization problems without the added complications and costs typically associated with quantum computing methods. The Digital Annealer computational architecture bridges the gap to the quantum world and paves the way for much faster, more efficient solving of today’s business problems. Our quantum-inspired computing solution is designed to solve large-scale combinatorial optimization problems which are unsolvable using today’s classical computers.
Quantum-Inspired Optimization Solutions: Toshiba SQBM+
https://www.global.toshiba/ww/products-solutions/ai-iot/sbm.html
Excerpt: For many social and industrial challenges, combinatorial optimization is essential for selecting the optimal items from an enormous range of choices; for example, optimizing financial transactions, the movement of industrial robots, travel and transmission routes, and molecular design for drug discovery. When using existing computers, combinatorial optimization is difficult to solve at high speeds because the number of combination patterns increases exponentially as the scale of the problem grows. For this reason, specialized combinatorial optimization computers are being actively developed in Japan and overseas.
The Simulated Bifurcation Machine, an Ising machine comprising Toshiba’s innovative quantum-inspired algorithms and corresponding computer solutions for solving combinatorial optimization problems, is the company’s star technology for bringing higher efficiencies to industry sectors that must make optimal complex decisions in short time spans, such as finance, logistics, and communications.
Fixstars Amplify AE
https://amplify.fixstars.com/en/engine#amplifyae
Excerpt: Fixstars Amplify Annealing Engine (AE) is a Graphics Processing Unit (GPU)-based annealing machine. It can process large-scale problems consisting of more than 100,000 bits at high speed. Although it is not based on quantum mechanical phenomena, it provides an ideal platform for easy PoC and development for practical applications, utilized for quantum annealing.
Optimization Software
The Leader in Decision Intelligence Technology | Gurobi Optimization
Excerpt: Your business faces extremely complex challenges. You need to achieve multiple, conflicting objectives simultaneously—amid an ever-changing business landscape and global disruption. That’s why 80% of the world’s leading enterprises turn to Gurobi’s decision intelligence technology.
Optimization Software | IBM
https://www.ibm.com/optimization-solver
Excerpt: Optimization solvers help improve decision-making around planning, allocating and scheduling scarce resources. They embed powerful algorithms that can solve mathematical programming models, constraint programming and constraint-based scheduling models.
IBM CPLEX® Optimizer solvers can find answers for linear programming, mixed integer programming, quadratic programming and quadratically constrained programming problems.
For detailed scheduling problems, IBM offers solvers designed for constraint-based scheduling models. For combinatorial problems such as a configuration or packing issue, you can build constraint programming models to solve them. And you can try the solvers at no charge.
Global Optimization Toolbox | MathWorks
https://www.mathworks.com/products/global-optimization.html
Excerpt: Global Optimization Toolbox provides functions that search for global solutions to problems that contain multiple maxima or minima. Toolbox solvers include surrogate, pattern search, genetic algorithm, particle swarm, simulated annealing, multistart, and global search. You can use these solvers for optimization problems where the objective or constraint function is continuous, discontinuous, stochastic, does not possess derivatives, or includes simulations or black-box functions. For problems with multiple objectives, you can identify a Pareto front using genetic algorithm or pattern search solvers.
COIN-OR: Computational Infrastructure for Operations Research – Open-source Software for the Operations Research Community
Excerpt: Without open source implementations of existing algorithms, testing new ideas built on existing ones typically requires the time-consuming and error-prone process of re-implementing (and re-debugging and re-testing) the original algorithm. If the original algorithm were publicly available in a community repository, imagine the productivity gains from software reuse! Science evolves when previous results can be easily replicated.
Quantum Annealing
D-Wave Systems | Quantum Realized
Excerpt: What problems could you solve with access to the largest quantum computers in the world? Whether you’re tackling operational challenges, advancing groundbreaking research, or even exploring new efficiencies with AI, D-Wave‘s annealing quantum computing technology is ready for real-world applications today.
Accelerating Research with a Unique Approach | NEC’s Quantum Computer Research
https://www.nec.com/en/global/rd/technologies/202307/index.html
Excerpt: Quantum computers use the gate-based method and quantum annealing. At NEC, we established a laboratory in collaboration with AIST where we are pursuing research and development into both types of quantum computers. In addition to making quantum annealing accessible from Tohoku University over the Internet, we have started joint research on future computer systems which utilize the features of both quantum annealing and simulated annealing.
Related Articles and Papers
Sutor Group Earnings Brief: D-Wave Quantum Announces Financial Results for Q4 2024 and FY 2024 – Sutor Group
Author: Bob Sutor
Date: Friday, March 14, 2025
Excerpt: Sutor Group Intelligence and Advisory examines the D-Wave Quantum financial results for Q4 2024 and FY 2024 and how they relate to AI and quantum technologies.
Sutor Group Intelligence and Advisory
Dr. Bob Sutor is the CEO and Founder of Sutor Group Intelligence and Advisory. Sutor Group provides broad market insights and deep technical expertise based on over four decades of experience with startups and large corporations. It advises Deep Tech startups, companies, and investors on quantum technologies, AI, and other emerging tech fields.
Sutor Group shares its knowledge and analysis through direct client engagements and seminars, reports, newsletters, books, written and on-air media appearances, and speaking and panel moderation at the top conferences and client events.
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