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BTQ Research Sees a Quantum Energy Advantage For Blockchain

Cryptocurrencies 6 mining rig components, blockchain details of technology. bitcoin, litecoin

Insider Brief

  • BTQ Technologies Corp. has published research highlighting the “Quantum Energy Advantage” in blockchain.
  • The work focuses on quantum computing’s ability to significantly reduce energy consumption, beyond its well-known speed capabilities.
  • A quantum proof-of-work (QPoW) algorithm that leverages quantum computing for blockchain technology, offering a practical solution to significantly lower the energy demands of cryptocurrencies.

PRESS RELEASE — BTQ Technologies Corp. (the “Company” or “BTQ”) (NEO CA: BTQ) (OTCQX: BTQQF) (FSE: NG3), a global quantum technology company focused on securing mission-critical networks, is pleased to announce groundbreaking research findings that redefine the energy efficiency paradigm in quantum computing. This significant advancement, discussed in an insightful blog post, introduces the concept of “Quantum Energy Advantage,” shifting the narrative from quantum computing’s speed capabilities to its potential in reducing energy consumption.

Historically, quantum computing has been heralded for its ability to solve problems at speeds unachievable by classical computing methods, a phenomenon often referred to as “quantum supremacy.” BTQ’s latest research, however, suggests that the real value of quantum computing lies in its superior energy efficiency. This revelation is crucial in an era where the energy demands of computational processes are skyrocketing.

The study delves into the fundamental differences between classical computing, which utilizes bits for information processing, and quantum computing, which operates with qubits. Qubits have the unique ability to exist in multiple states simultaneously due to the principle of quantum superposition. This characteristic enables quantum computers to tackle certain computational problems with exponentially lower energy consumption than classical computers, particularly in areas where traditional computing methods falter due to complexity.

One of the most compelling aspects of BTQ’s research is its application to the blockchain technology sector, specifically concerning the energy-intensive proof-of-work (PoW) mechanism utilized by cryptocurrencies like Bitcoin. By implementing boson-sampling, a method in quantum computing, BTQ researchers have developed a quantum proof-of-work (QPoW) algorithm that dramatically reduces the energy expenditure required for blockchain transactions. This innovation not only exemplifies a practical use case for quantum computing but also addresses a significant environmental concern associated with blockchain technology.

“Our findings mark a pivotal moment in the exploration of quantum computing, highlighting its potential to revolutionize both computational speed and energy efficiency,” stated Olivier Roussy Newton, CEO of BTQ. “The application of quantum computing in reducing the environmental impact of digital networks exemplifies our commitment to leveraging cutting-edge technology for solving real-world problems. We stand on the brink of a new computing era, where quantum technology not only enhances performance but also champions sustainability.”

For more market insights, check out our latest quantum computing news here.

The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

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Matt Swayne

With a several-decades long background in journalism and communications, Matt Swayne has worked as a science communicator for an R1 university for more than 12 years, specializing in translating high tech and deep tech for the general audience. He has served as a writer, editor and analyst at The Quantum Insider since its inception. In addition to his service as a science communicator, Matt also develops courses to improve the media and communications skills of scientists and has taught courses. [email protected]

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The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

Picture of Jake Vikoren

Jake Vikoren

Company Speaker

Picture of Deep Prasad

Deep Prasad

Company Speaker

Picture of Araceli Venegas

Araceli Venegas

Company Speaker

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