SQBM+ is a quantum-inspired optimization solution based on the Simulated Bifurcation Machine (SBM) that is a combinatorial optimization solver utilizing the Simulated Bifurcation Algorithm (SB Algorithm) developed by Toshiba Corporation. We offer a lineup of optimization solvers according to the intended application and have adopted a new SB Algorithm that greatly improves speed, accuracy, and scale.

Combinatorial optimization is an essential tool for addressing a wide range of social and industrial challenges that identifies optimal solutions from an enormous range of choices. Its diverse applications span domains that include financial decision-making, operating industrial robots, logistics, route planning, power grid optimization, and molecular level drug discovery. However, as the scale of any given problem expands, triggering an exponential increase in combination patterns, finding solutions on computers with a standard classical architecture becomes increasingly challenging. Companies around the world are addressing this problem by developing dedicated computers for combinatorial optimization.

In contrast, SQBM+ runs on standard computers and finds high-precision, approximate solutions (high-quality solutions) to complex, large-scale problems in a short time. The commercial launch of SQBM+ allowed Toshiba and its partners to verify the practicality of SQBM+ and the effectiveness of applying quasi-quantum computing to high-speed, high-frequency stock trading, computational drug discovery, energy management, and materials development.

We have been searching for real problems to solve issues in a variety of fields by cooperating with research institutions such as universities, as well as with corporations aiming to solve social issues as actual problems in combinatorial optimization. We provide systematized SQBM+ as a solution by utilizing the results of business co-creation efforts aimed at developing new markets and creating new solutions by using SBM technology, as well as the knowledge gained through various verification experiments in Japan and overseas. SQBM is an acronym for “Simulated Quantum-inspired Bifurcation Machine,” which means that it is derived from SBM that implements the SB Algorithm invented in the research process for quantum computers at Toshiba's R&D centers. The “+” indicates that this solution includes various services and indicates our intention to continuously strengthen the solution.

we provide execution modules on the current AWS Marketplace. We also plan to provide on-premise versions for highly-confidential applications unsuitable for cloud environments and applications that require low latency and to embed those versions in partner applications or provide them on an OEM basis. Furthermore, we will provide professional services such as education and support for formulation.

SQBM+ Version 2 can address larger scale problems related to investment portfolio management and drug development. we aim to leverage SQBM+ across numerous fields and to contribute to the resolution of complicated issues.

Toshiba’s original Ising machine: Fast, Large-scale, Available Now

Quantum inspired algorithm

Totally new algorithm derived from the research of Toshiba’s quantum computer “quantum bifurcation machine”
Utilizes the new method of classical adiabatic exploration and ergodic exploration

Fast and Large-scale
- Published in “Science Advances”

Available Now

Can be implemented on the general servers
- normal temperature, normal power supply -

FPGA implementation GPU implementation

Intel^®FPGA

Features of SQBM+

Can handle 10 million variables and solve large-scale problems

SQBM+ Version 2 supports a Quadratic Unconstrained Binary Optimization (QUBO) solver capable of handling QUBO problems with up to 10 million variables.

Adopts a new algorithm that significantly improves speed, accuracy, and scale

lBallistic Simulated Bifurcation Algorithm (bSB): A high-speed algorithm for finding a good solution in a short time.
lDiscrete Simulated Bifurcation Algorithm (dSB): A high-accuracy algorithm for finding more accurate solutions at a calculation speed that surpasses that of other machines.
lIncludes a function that automatically selects and uses one of the two algorithms listed above.

Provides optimization solvers according to the intended application

In addition to the general-purpose QUBO solver, we also offer solvers designed for specific purposes. This provides mechanisms/routes for securing easy and direct solutions to specific problems.

QUBO solver
A general-purpose solver, the basic solver of SQBM+, which uses the SB Algorithm to solve combinatorial optimization problems expressed in the format of quadratic unconstrained binary optimization (QUBO).
TSP solver
A solver that directly solves the traveling-salesman type problems without expressing the solution in QUBO.
SHIFT solver
A solver that directly solves shift scheduling problems, such as assigning jobs to employees while considering various constraints, without using QUBO.
QAP solver
A solver that directly solves quadratic assignment problems (QAP) without expressing them in QUBO. For example, the optimal placement of facilities to minimize the cost of transporting goods between them.

Expansion of application range

We have enhanced SQBM+ capabilities by offering extended functions and solvers to improve usability and overall performance.

Parameter automatic adjustment function/solver
Automates the tuning of unique SBM parameters and quickly finds better solutions without the hassle of manual adjustment. There is an automatic adjustment function for each parameter and an Ising solver that eliminates the need to adjust any of the parameters.
PUBO solver
A solver that supports cubic and quartic problems. Real-life combinatorial optimization problems may contain cubic or higher terms. Solving such problems with the QUBO solver requires conversion to quadratic expressions, which may degrade performance. SQBM+ Version 2 uses the capabilities of the SB Algorithm to support these higher-order terms, and to achieve higher-level solution performance for real-life combinatorial optimization problems.
QPLIB solver
For linearly constrained quadratic binary programming problems. It supports QPLIB as input data format.
QP solver
A solver that can directly solve quadratic binary optimization problems with linear constraints. Compared to solving similar problems with the Ising solver, there is no need to incorporate linear constraints into QUBO and adjust penalty parameters, thus making it easier to obtain highly-accurate solutions.
Enabling continuous variables
Real-life combinatorial optimization problems may contain continuous variables. Solving such problems with the QUBO solver requires conversion to quadratic expressions and binary variables, which is a factor in degrading the equation solution performance. SQBM+ will utilize the features of the SB Algorithm to support continuous variables, and to achieve higher solution performance for real-life combinatorial optimization problems.