{"id":118534,"date":"2020-09-24T16:17:43","date_gmt":"2020-09-24T16:17:43","guid":{"rendered":"https:\/\/news.microsoft.com\/?p=439210"},"modified":"2020-09-24T16:17:43","modified_gmt":"2020-09-24T16:17:43","slug":"toshiba-joins-azure-quantum-providing-machine-to-solve-complex-optimization-problems","status":"publish","type":"post","link":"https:\/\/sickgaming.net\/blog\/2020\/09\/24\/toshiba-joins-azure-quantum-providing-machine-to-solve-complex-optimization-problems\/","title":{"rendered":"Toshiba joins Azure Quantum, providing machine to solve complex optimization problems"},"content":{"rendered":"
<\/div>\n

Complex optimization problems exist across every industry, such as vehicle routing, supply chain management, risk <\/span>assessment<\/span>, portfolio optimization, power grid <\/span>operations<\/span>, and many others. <\/span> <\/span><\/p>\n

While a number of sophisticated algorithms have been developed that can solve certain optimization problems very efficiently, many real-world optimization problems remain hard to optimize despite the remarkable advancements in both algorithms and computing power over the past decades. These scenarios usually involve many variables and are computationally difficult to solve using traditional methods.<\/span> <\/span><\/p>\n

Leveraging quantum methods <\/span>allows us to <\/span>find more accurate <\/span>solutions <\/span>in far less time with much less work, even for the most complex problems.<\/span> <\/span>In practice, emulating quantum systems has led to promising breakthroughs<\/span> in <\/span>MRI technology<\/span><\/a>, <\/span>improving traffic congestion<\/span><\/a>, <\/span>material<\/span>s<\/span> design<\/span><\/a>, and more.<\/span> <\/span><\/p>\n

Emulating nature with Azure Quantum<\/h2>\n

Many optimization algorithms, such as simulated annealing, parallel tempering Monte Carlo, or genetic algorithms<\/span>,<\/span> mimic natural processes. <\/span>As we\u2019ve developed a deeper understanding of quantum mechanics, new<\/span> optimizers have been developed that make use of quantum mechanics to accelerate optimization and escape local minima in the cost function landscape through <\/span>emulating <\/span>quantum tunneling.<\/span> <\/span><\/p>\n

Simulating<\/span> <\/span>these quantum effects on classical computers has led to the development of new types of quantum solutions that run on classical hardware, also called quantum-inspired optimization (QIO) algorithms. These algorithms allow us to exploit some of the advantages of quantum computing approaches today on classical CMOS-based hardware, providing a speedup over traditional approaches. Using quantum solutions on classical hardware also prepares us for the future of quantum optimization on <\/span>scaled<\/span>, fault-tolerant<\/span> <\/span>quantum hardware.<\/span> <\/span> <\/span><\/p>\n

Azure Quantum enables customers to run optimization algorithms on industry-scale <\/span>classical <\/span>hardware <\/span>with<\/span> self-service solutions designed to solve <\/span>binary <\/span>optimization <\/span>problems <\/span>on CPUs, GPUs, and FPGAs in Azure<\/span>.<\/span> <\/span> <\/span><\/p>\n

Toshiba offering Simulated Bifurcation Machine through Azure Quantum<\/h2>\n

Expanding the<\/span> portfolio of QIO algorithms and solvers, Microsoft is pleased to announce that Toshiba is joining the Microsoft Quantum Network<\/span> and will be offering <\/span>Toshiba\u2019s Simulated Bifurcation Machine (SBM) in Azure Quantum<\/span>. Toshiba joins<\/span> <\/span>existing partners <\/span>1Qbit, Honeywell, <\/span>IonQ<\/span>, and QCI<\/span> in providing services to <\/span>the growing <\/span>quantum <\/span>ecosystem.<\/span> <\/span><\/p>\n

Toshiba\u2019s<\/span> cutting-edge<\/span> technique quickly obtains highly accurate solutions for complex large-scale combinatorial optimization problems and <\/span>has demonstrated <\/span>an approximately 10-fold improvement over other competing devices. Some examples of combinatorial optimization problems <\/span>include <\/span>dynamic portfolio management<\/span>, risk management,<\/span> and high-frequency trading. Practical applications include <\/span>optimizing routing for <\/span>electrical transmission lines considering cost, safety, time, and environmental impact; or finding the shortest route between cities, considering the time of day, traffic incidents, and driver schedule. <\/span> <\/span><\/p>\n

In principle<\/span>,<\/span> every <\/span>computational <\/span>problem we see in practice can be <\/span>translated<\/span> to <\/span>a particular type of binary optimization <\/span>problem<\/span>: searching for the ground state of an <\/span>Ising<\/span> model. <\/span>While<\/span>,<\/span> in general<\/span>,<\/span> this mapping can be too costly to be practical, combinatorial optimization<\/span> <\/span>problems <\/span>are <\/span>often <\/span>easy to rewrite into<\/span> this form<\/span>,<\/span> and <\/span>for problems that are native to this form<\/span> (such as <\/span>planning, scheduling, <\/span>or<\/span> partitioning<\/span>), <\/span>techniques such <\/span>as <\/span>those employed by <\/span>Toshiba\u2019s solution<\/span> provide a powerful tool for solving them.<\/span> <\/span><\/p>\n

Emerging from quantum computing research at Toshiba, SBM is a practical and ready-to-use <\/span>Ising<\/span> model solver\u2014<\/span>a software solution that is able to solve large-scale combinatorial optimization problems at high speed, while harnessing the GPU resources in the Azure cloud.<\/span> <\/span><\/p>\n

Azure Quantum users will soon be able to utilize the Toshiba SBM to explore<\/span> <\/span>highly accurate<\/span> <\/span>solutions using quantum methods <\/span>for their own <\/span>scenarios<\/span>.<\/span> <\/span><\/p>\n

Build quantum solutions today<\/h2>\n

Azure Quantum<\/span><\/a> <\/span>is an open ecosystem of quantum partners and technologies. Building on decades of quantum research and scalable enterprise cloud offerings<\/span> at Microsoft<\/span>, <\/span>Azure Quantum<\/span> <\/span>brings you rich software capabilities<\/span> and development tools paired with quantum and classical <\/span>hardware<\/span> <\/span>through a familiar Azure environment<\/span>.<\/span> <\/span><\/p>\n

With <\/span>our ever-growing <\/span>offerings<\/span>,<\/span> <\/span>like Toshiba\u2019s SBM, <\/span>a<\/span>chieve immediate impact with quantum-inspired optimization running on classical hardwar<\/span>e today and build for tomorrow with quantum hardware.<\/span> <\/span>Sign up to become an <\/span>Azure Quantum<\/span> early adopter<\/span><\/a>.<\/span> <\/span><\/p>\n

Join us <\/span><\/h2>\n

With this announcement, w<\/span>e are excited to welcome Toshiba to the <\/span>Microsoft Quantum Network<\/span><\/a>. <\/span>The <\/span>Microsoft Quantum Network<\/span> <\/span>is <\/span>a broad community of individuals and organizations collaborating with Microsoft to advance a comprehensive quantum ecosystem, develop practical solutions, and build a robust quantum workforce.<\/span> <\/span> <\/span><\/p>\n

To build this right, we need to build it together. <\/span> <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n

 <\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Complex optimization problems exist across every industry, such as vehicle routing, supply chain management, risk assessment, portfolio optimization, power grid operations, and many others.   While a number of sophisticated algorithms have been developed that can solve certain optimization problems very efficiently, many real-world optimization problems remain hard to optimize despite the remarkable advancements in both algorithms and […]<\/p>\n","protected":false},"author":2,"featured_media":118535,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[49],"tags":[139,50],"class_list":["post-118534","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-microsoft-news","tag-quantum-computing","tag-recent-news"],"_links":{"self":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/posts\/118534","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/comments?post=118534"}],"version-history":[{"count":0,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/posts\/118534\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/media\/118535"}],"wp:attachment":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/media?parent=118534"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/categories?post=118534"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/tags?post=118534"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}