Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Quantum Computers Managed To Surpass Ordinary Computers

Sara Krish

Published Jan 1, 2021• 0 citations
OpenAlex

Abstract

Interest in constructing quantum computer systems has received big momentum in latest years, and feverish work is underway in many components of the world. In 2019, Google's lookup group made a foremost leap forward when their quantum pc managed to resolve a undertaking a ways extra shortly than the world's great supercomputer.

Related papers

Aggregated Control of Quantum Computations: When Stacked Architectures Are Too Good to Be Practical Soon

Alexandru Paler

Google's quantum supremacy demonstration pitted the world's largest supercomputer against a single quantum chip. A path to further scaleup may involve a large supercomputer working together withquantum chips, instead of in competition with them.

Computer•Jul 30, 2020•1 citation

Making the quantum leap

Roger Dettmer, S. Josifovska

With quantum computing, we're potentially at the threshold of a revolution in information processing every bit as big as that initiated by the invention of the transistor. If we can develop a quantum computer, we'll be able to do calculations that would be impossible using all the conventional computers in the world working together. True, there are formidable problems, but we have to believe they can be overcome. Do quantum mechanical effects pose a fundamental threat to continued progress in microelectronics? Key world laboratories say 'no'.

IEE Review•Jun 1, 2003•1 citation

Google uncovers how quantum computers can beat today’s best supercomputers

Dan Garisto

Nature•Oct 9, 2024•6 citations

Quantum leap for quantum computing

JR Minkel

This paper reports on a promising technology for constructing an ultrapowerful quantum computer, called the ion trap. Researchers have found a way to build ion traps from semiconductors in much the same way as computer chips. By linking several of these ion trap chips, researchers are able to manipulate much larger numbers of ions and demonstrate rudimentary components of a quantum computer over the next few years. A major benefit of chip-based ion traps is that they could be combined into large arrays. The goal is to create a big switchyard in which hundreds or thousands of ions are constantly being shuttled around in small groups, controlled by conventional electronics.

IEEE Spectrum•Mar 1, 2006•2 citations

Simulation of Quantum Circuits Using the Big-Batch Tensor Network Method

Feng Pan, Pan Zhang

We propose a tensor network approach to compute amplitudes and probabilities for a large number of correlated bitstrings in the final state of a quantum circuit. As an application, we study Google's Sycamore circuits, which are believed to be beyond the reach of classical supercomputers and have been used to demonstrate quantum supremacy. By employing a small computational cluster containing 60 graphical processing units (GPUs), we compute exact amplitudes and probabilities of 2×10^{6} correlated bitstrings with some entries fixed (which span a subspace of the output probability distribution) for the Sycamore circuit with 53 qubits and 20 cycles. The obtained results verify the Porter-Thomas distribution of the large and deep quantum circuits of Google, provide datasets and benchmarks for developing approximate simulation methods, and can be used for spoofing the linear cross entropy benchmark of quantum supremacy. Then we extend the proposed big-batch method to a full-amplitude simulation approach that is more efficient than the existing Schrödinger method on shallow circuits and the Schrödinger-Feynman method in general, enabling us to obtain the state vector of Google's simplifiable circuit with n=43 qubits and m=14 cycles using only one GPU. We also manage to obtain the state vector for Google's simplifiable circuits with n=50 qubits and m=14 cycles using a small GPU cluster, breaking the previous record on the number of qubits in full-amplitude simulations. Our method is general in computing bitstring probabilities for a broad class of quantum circuits and can find applications in the verification of quantum computers. We anticipate that our method will pave the way for combining tensor network-based classical computations and near-term quantum computations for solving challenging problems in the real world.

Physical Review Letters•Jan 19, 2022•154 citations

Practical quantum computers still at least a decade away

Peter H. Gwynne

Significant technical and financial issues remain towards building a large, fault-tolerant quantum computer and one is unlikely to be built within the coming decade.

Physics World•Jan 1, 2019•2 citations
With quantum computing, we're potentially at the threshold of a revolution in information processing every bit as big as that initiated by the invention of the transistor. If we can develop a quantum computer, we'll be able to do calculations that would be impossible using all the conventional computers in the world working together. True, there are formidable problems, but we have to believe they can be overcome. Do quantum mechanical effects pose a fundamental threat to continued progress in microelectronics? Key world laboratories say 'no'.
This paper reports on a promising technology for constructing an ultrapowerful quantum computer, called the ion trap. Researchers have found a way to build ion traps from semiconductors in much the same way as computer chips. By linking several of these ion trap chips, researchers are able to manipulate much larger numbers of ions and demonstrate rudimentary components of a quantum computer over the next few years. A major benefit of chip-based ion traps is that they could be combined into large arrays. The goal is to create a big switchyard in which hundreds or thousands of ions are constantly being shuttled around in small groups, controlled by conventional electronics.
We propose a tensor network approach to compute amplitudes and probabilities for a large number of correlated bitstrings in the final state of a quantum circuit. As an application, we study Google's Sycamore circuits, which are believed to be beyond the reach of classical supercomputers and have been used to demonstrate quantum supremacy. By employing a small computational cluster containing 60 graphical processing units (GPUs), we compute exact amplitudes and probabilities of 2×10^{6} correlated bitstrings with some entries fixed (which span a subspace of the output probability distribution) for the Sycamore circuit with 53 qubits and 20 cycles. The obtained results verify the Porter-Thomas distribution of the large and deep quantum circuits of Google, provide datasets and benchmarks for developing approximate simulation methods, and can be used for spoofing the linear cross entropy benchmark of quantum supremacy. Then we extend the proposed big-batch method to a full-amplitude simulation approach that is more efficient than the existing Schrödinger method on shallow circuits and the Schrödinger-Feynman method in general, enabling us to obtain the state vector of Google's simplifiable circuit with n=43 qubits and m=14 cycles using only one GPU. We also manage to obtain the state vector for Google's simplifiable circuits with n=50 qubits and m=14 cycles using a small GPU cluster, breaking the previous record on the number of qubits in full-amplitude simulations. Our method is general in computing bitstring probabilities for a broad class of quantum circuits and can find applications in the verification of quantum computers. We anticipate that our method will pave the way for combining tensor network-based classical computations and near-term quantum computations for solving challenging problems in the real world.