What Drove Quantum Computing (QUBT) Stock Higher In The Last Trading?

Shares of Quantum Computing Inc (OTC: QUBT) closed the past session higher by 19.48% to $7.8860. 199.72K shares of Quantum Computing stock were traded during the session, with the QUBT stock price ranging from $6.6000 to $8.4000. News of the launch of cloud-based software focused on graphs sent the QUBT stock soaring.

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What was the news?

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Quantum Computing is focused on maximizing the benefits of quantum computing in real-world business applications. Using Qatalyst, the company’s flagship product, SMEs can solve complex computational problems easily, hiding complexity and solving fundamental problems through quantum computing. Experts at QUBT are vastly experienced and have worked on the most advanced supercomputing systems, have vast experience in massively parallel programming, and designed technology that protects nations.

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Quantum Computing has launched QGraph, which analyzes graphs with QCI’s Qatalyst quantum software on the cloud, revealed QUBT in a press release yesterday.

  • With graph and Qatalyst, users and analysts can solve the hardest computationally expensive graph problems, taking advantage of quantum computing to the fullest extent.
  • These are crucial for understanding high-dimensional data in fast-moving circumstances, and they have been prohibitively expensive to compute to date.
  • On both classical and quantum computers, these techniques are quick and cost-effective.
  • The graph application makes use of the powerful Q API to solve the most challenging graph kernels.
  • By transforming input graphs into constrained optimization problems, Qatalyst Core delivers these to the QPU for processing and analyzing.
  • These techniques also deliver increased accuracy and diversity of results due to quantum-ready capabilities.
  • An effective way to visualize heterogeneous data with many dimensions, unstructured values, and sparse values is with graphs.

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  • In addition to modeling social, metabolic, gene, and transportation networks, graphs are also used to model molecular structures.

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