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Scientific American

Light-Based Quantum Computer Exceeds Fastest Classical Supercomputers

Daniel Garisto

Published Feb 1, 2021• 2 citations
Publisher
DOI
10.1038/scientificamerican022021-6zmcyq2phjda0uddjotyjd

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Supercomputers are making rapid progress. For the world's fastest supercomputer “Frontier,” the computing speed has reached 10 trillion floating-point instruction cycles per second (1018, exaFLOPS), making many existing complex problems, including weather forecasting and disaster prevention, more accurate than ever. However, the calculation of real systems with a large number of electrons is still difficult. Exascale computers can simulate some systems with dual quantum states, but in the case ofndual quantum states, the exponential growth of 2nmakes the calculation to simulate real system impossible. If we want to understand the dynamic quantum state evolution of a real matter, it is even more difficult to track the dynamics of “every possible” configuration of a huge number of 2nquantum states. If n is 20, it will take about 128 KB of memory to store with the current computer's memory, which can be done by ordinary computers. When there are hundreds of electrons, the memory required to store this system exceeds the number of particles in the entire universe. Unfortunately, almost all materials and drugs have at least hundreds of electrons, which means that direct use of Exascale computers to develop and design any new drugs and materials also becomes impossible. At the same time, after the popularization of artificial intelligence and deep learning, it is also found that the computing power, bandwidth, and memory space of classical computers are not enough, while quantum computing has at least the following three advantages and has the opportunity to provide solutions for complex systems.

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The Hidden River: Why Quantum Computers Are Already Extracting Energy from the Quantum Ocean, and How to Prove It

Dr Akshay Honrao, BDS,PGDIP(Orthodontics)

Google's Willow quantum processor completes a Random CircuitSampling (RCS) benchmark in under five minutes that would take themost powerful classical supercomputer an estimated 10²⁵ years. Thecomputation is physically real — the result is correct, verifiable, andreproducible. This paper poses a question that has not been asked:where does the energy for this computation come from? Landauer'sprinciple (1961, experimentally verified 2012) establishes thatcomputation has a minimum thermodynamic cost: E_min = kT ln 2 perbit of information erased. The classical equivalent of Willow'scomputation would require energy far exceeding what Willow consumes.If the computation is real, and if Landauer's principle is universal, thenthe energy deficit must be supplied by an external source. This paperidentifies that source as the quantum ocean (Parts 27–37). We arguethat quantum computational speedup is not merely an algorithmic trick— it is ocean-subsidised computation, where the energy differencebetween classical and quantum execution is supplied by the ocean'svacuum energy (~10⁹³ g/cm³) through the pre-Big-Bang entanglementchannel established in Part 36. The energy manifests as computationalspeed rather than electrical power — a phenomenon we term theHidden River Principle. We propose a definitive experimental test:precision calorimetry on quantum computers to measure the energybudget of quantum versus classical computation. If the quantumcomputation's energy output (measured as work done) exceeds theenergy input (measured as electricity consumed) beyond all knowninternal sources, this constitutes direct evidence for an externalenergy reservoir — the quantum ocean. This experiment requires nonew technology, no space telescopes, and no underground detectors. Itcan be performed on existing hardware with existing calorimetrictechniques, making it the cheapest, fastest, and most direct test of thequantum ocean hypothesis. 🌌 Interactive Space Research Assistant: Explore and ask questions about this research interactively with the Quantum Ocean Framework Ai Chat (or talk directly with the Quantum Ocean Framework Ai voice conversation).

•Sep 2, 2026•0 citations
Supercomputers are making rapid progress. For the world's fastest supercomputer “Frontier,” the computing speed has reached 10 trillion floating-point instruction cycles per second (1018, exaFLOPS), making many existing complex problems, including weather forecasting and disaster prevention, more accurate than ever. However, the calculation of real systems with a large number of electrons is still difficult. Exascale computers can simulate some systems with dual quantum states, but in the case ofndual quantum states, the exponential growth of 2nmakes the calculation to simulate real system impossible. If we want to understand the dynamic quantum state evolution of a real matter, it is even more difficult to track the dynamics of “every possible” configuration of a huge number of 2nquantum states. If n is 20, it will take about 128 KB of memory to store with the current computer's memory, which can be done by ordinary computers. When there are hundreds of electrons, the memory required to store this system exceeds the number of particles in the entire universe. Unfortunately, almost all materials and drugs have at least hundreds of electrons, which means that direct use of Exascale computers to develop and design any new drugs and materials also becomes impossible. At the same time, after the popularization of artificial intelligence and deep learning, it is also found that the computing power, bandwidth, and memory space of classical computers are not enough, while quantum computing has at least the following three advantages and has the opportunity to provide solutions for complex systems.
Abstract Noisy intermediate-scale quantum (NISQ) computers are entering an era in which they can perform computational tasks beyond the capabilities of the most powerful classical computers, thereby achieving ‘quantum supremacy’, a major milestone in quantum computing. NISQ supremacy requires comparison with a state-of-the-art classical simulator. We report HPC simulations of hard random quantum circuits (RQC), which have been recently used as a benchmark for the first experimental demonstration of quantum supremacy, sustaining an average performance of 281 Pflop/s (true single precision) on Summit, currently the fastest supercomputer in the world. These simulations were carried out using qFlex, a tensor-network-based classical high-performance simulator of RQCs. Our results show an advantage of many orders of magnitude in energy consumption of NISQ devices over classical supercomputers. In addition, we propose a standard benchmark for NISQ computers based on qFlex.
Google's Willow quantum processor completes a Random CircuitSampling (RCS) benchmark in under five minutes that would take themost powerful classical supercomputer an estimated 10²⁵ years. Thecomputation is physically real — the result is correct, verifiable, andreproducible. This paper poses a question that has not been asked:where does the energy for this computation come from? Landauer'sprinciple (1961, experimentally verified 2012) establishes thatcomputation has a minimum thermodynamic cost: E_min = kT ln 2 perbit of information erased. The classical equivalent of Willow'scomputation would require energy far exceeding what Willow consumes.If the computation is real, and if Landauer's principle is universal, thenthe energy deficit must be supplied by an external source. This paperidentifies that source as the quantum ocean (Parts 27–37). We arguethat quantum computational speedup is not merely an algorithmic trick— it is ocean-subsidised computation, where the energy differencebetween classical and quantum execution is supplied by the ocean'svacuum energy (~10⁹³ g/cm³) through the pre-Big-Bang entanglementchannel established in Part 36. The energy manifests as computationalspeed rather than electrical power — a phenomenon we term theHidden River Principle. We propose a definitive experimental test:precision calorimetry on quantum computers to measure the energybudget of quantum versus classical computation. If the quantumcomputation's energy output (measured as work done) exceeds theenergy input (measured as electricity consumed) beyond all knowninternal sources, this constitutes direct evidence for an externalenergy reservoir — the quantum ocean. This experiment requires nonew technology, no space telescopes, and no underground detectors. Itcan be performed on existing hardware with existing calorimetrictechniques, making it the cheapest, fastest, and most direct test of thequantum ocean hypothesis. 🌌 Interactive Space Research Assistant: Explore and ask questions about this research interactively with the Quantum Ocean Framework Ai Chat (or talk directly with the Quantum Ocean Framework Ai voice conversation).