{"id":62898,"date":"2026-04-07T10:02:22","date_gmt":"2026-04-07T08:02:22","guid":{"rendered":"https:\/\/pharma-trend.com\/en\/toshibas-breakthrough-algorithm-harnesses-edge-of-chaos-to-dramatically-boost-performance-of-its-quantum-inspired-computer\/"},"modified":"2026-04-07T10:02:22","modified_gmt":"2026-04-07T08:02:22","slug":"toshibas-breakthrough-algorithm-harnesses-edge-of-chaos-to-dramatically-boost-performance-of-its-quantum-inspired-computer","status":"publish","type":"post","link":"https:\/\/pharma-trend.com\/en\/toshibas-breakthrough-algorithm-harnesses-edge-of-chaos-to-dramatically-boost-performance-of-its-quantum-inspired-computer\/","title":{"rendered":"Toshiba\u2019s Breakthrough Algorithm Harnesses Edge of Chaos to Dramatically Boost Performance of its Quantum\u2011Inspired Computer"},"content":{"rendered":"
\n

\n~Approximately 100 times faster, will accelerate solutions for drug discovery, finance, and other complex problems~<\/i><\/p>\n

KAWASAKI, Japan–(BUSINESS WIRE)–#SBM<\/a>–Toshiba Corporation has developed a breakthrough algorithm that dramatically boosts the performance of the Simulated Bifurcation Machine (SBM), its proprietary quantum\u2011inspired combinatorial optimization computer. The new algorithm significantly improves the probability of obtaining an optimal solution or a known best solution within a limited number of trials\u2014referred to as the success probability, a key benchmark for evaluating combinatorial optimization technologies.<\/p>\n

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\nThe SBM is designed to solve large\u2011scale combinatorial optimization problems in a wide range of fields, including new drug discovery, delivery route optimization, and investment portfolio design. While previous algorithms could find optimal or known best solutions with a sufficiently large number of trials, large\u2011scale problems often trapped the search process in local optima, significantly lowering success probability under practical constraints that limit the number of trials.<\/p>\n

\nToshiba has overcome this challenge by developing a third\u2011generation simulated bifurcation (SB) algorithm. This ground-breaking advance builds on the original SB algorithm, announced in April 2019*1<\/sup>, and the second\u2011generation SB algorithm, released in February 2021*2<\/sup>, which delivered major boosts to computational speed and accuracy.<\/p>\n

\nThe new algorithm expands the bifurcation parameter that triggers the bifurcation phenomena*3<\/sup>\u2014a defining feature of the SB algorithm\u2014from a single global parameter to individual parameters assigned to each position variable*4<\/sup>. These bifurcation parameters are independently controlled according to the values of the corresponding position variables, enabling a more adaptive and effective solution search.<\/p>\n

\nWith the introduction of this advanced control mechanism, the algorithm exhibits either regular or chaotic behavior*5<\/sup>, depending on conditions. Crucially, Toshiba discovered that by effectively harnessing chaos at the edge of chaos<\/i>\u2014the boundary between regular dynamics and chaotic motion\u2014the algorithm can escape local optima far more efficiently. As a result, the success probability of reaching the global optimum increases dramatically, approaching 100%.<\/p>\n

\nThe SBM based on the new algorithm is therefore much faster. It delivers a time to solution (TTS) required to obtain an optimal or known best solution that is approximately 100 times faster than the SBM based on the second\u2011generation algorithm. These advances are expected to accelerate the practical applications of combinatorial optimization across a broad range of challenges.<\/p>\n

\nThe research results were published in the April 6, 2026 issue of Physical Review Applied, a peer\u2011reviewed journal of the American Physical Society*6.<\/sup><\/p>\n

\nNote:
\n
*1 https:\/\/advances.sciencemag.org\/content\/5\/4\/eaav2372<\/a>
*2 https:\/\/advances.sciencemag.org\/content\/7\/6\/eabe7953<\/a>
*3 In nonlinear dynamical systems, a phenomenon in which changes in system parameters (bifurcation parameters) cause the number of stable points to change from one to multiple.
\n
*4 In the SB algorithm, the equations of motion of a classical dynamical system consisting of many oscillators are solved. A position variable represents the position of each oscillator, and these position variables correspond to the decision variables (discrete variables) of the combinatorial optimization problem.
\n
*5 In nonlinear dynamical systems, a phenomenon in which even slight differences in initial conditions cause the subsequent trajectories of motion to diverge significantly, resulting in disordered (chaotic) behavior. This sensitivity of chaos to initial conditions is known as the butterfly effect, and the upper panel of Figure 1 provides a quantitative evaluation of this effect.
\n
*6 https:\/\/doi.org\/10.1103\/2qd9-x6v8<\/a><\/p>\n

\nAbout Toshiba
\n
<\/span><\/b>For over 150 years, guided by its corporate philosophy, \u201cCommitted to People, Committed to the Future.,\u201d Toshiba Group has contributed to society through its business activities. Today, the Group continues to enhance its management structure, streamline operations, and invest in forward\u2011looking businesses in the energy, digital infrastructure, and electronic devices domains.
\n
Annual sales in fiscal year 2025 were 3.5 trillion yen, with 95,000 employees worldwide. Find out more on our website<\/a> or follow us on LinkedIn<\/a>.<\/p>\n

Contacts<\/b> <\/p>\n

\nToshiba Corporation<\/b>
Media Relations Office<\/b>
Ryoji Shinohara\/Naoko Oura
\n
media.relations@toshiba.co.jp<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

~Approximately 100 times faster, will accelerate solutions for drug discovery, finance, and other complex problems~ KAWASAKI, Japan–(BUSINESS WIRE)–#SBM–Toshiba Corporation has developed a breakthrough algorithm that dramatically boosts the performance of the Simulated Bifurcation Machine (SBM), its proprietary quantum\u2011inspired combinatorial optimization computer. The new algorithm significantly improves the probability of obtaining an optimal solution or a … [Read more…]<\/a><\/span><\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[13],"tags":[],"class_list":{"0":"entry","1":"post","2":"publish","3":"author-business","4":"post-62898","6":"format-standard","7":"category-industry"},"yoast_head":"\nToshiba\u2019s Breakthrough Algorithm Harnesses Edge of Chaos to Dramatically Boost Performance of its Quantum\u2011Inspired Computer - Pharma Trend<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/pharma-trend.com\/en\/toshibas-breakthrough-algorithm-harnesses-edge-of-chaos-to-dramatically-boost-performance-of-its-quantum-inspired-computer\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Toshiba\u2019s Breakthrough Algorithm Harnesses Edge of Chaos to Dramatically Boost Performance of its Quantum\u2011Inspired Computer - Pharma Trend\" \/>\n<meta property=\"og:description\" content=\"~Approximately 100 times faster, will accelerate solutions for drug discovery, finance, and other complex problems~ KAWASAKI, Japan–(BUSINESS WIRE)–#SBM–Toshiba Corporation has developed a breakthrough algorithm that dramatically boosts the performance of the Simulated Bifurcation Machine (SBM), its proprietary quantum\u2011inspired combinatorial optimization computer. 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