Skip to main content
Admissions guidance, study banks, and career tools — get started on Shalyam
Research News

Ordinary Laptop Solves Quantum Problem Thought to Need Supercomputer

Mayur Tembhare
  1. Researchers at the Center for Computational Quantum Physics used an ordinary laptop to solve a difficult quantum problem.

  2. The method uses advanced mathematics and specialized software to compress the information contained in the wave function of the quantum system.

  3. The team's approach can now be used to study more quantum dynamics problems and may offer a strategy for optimization problems.

  4. The findings were published in the journal Science on May 21, 2026.

Ordinary Laptop Solves Quantum Problem Thought to Need Supercomputer

Topic: Physics

Physicists at the Center for Computational Quantum Physics used an ordinary laptop and advanced math to solve a complex quantum problem that was previously thought to require a supercomputer. Their method can now be used to study more quantum dynamics problems.

Physicists have made a breakthrough in solving a difficult quantum physics problem using an ordinary computer, advanced mathematics, and specialized software. The researchers at the Center for Computational Quantum Physics (CCQ) at the Simons Foundation's Flatiron Institute worked with collaborators at Boston University to develop a new method that can solve complex quantum problems efficiently.

The challenge involved modeling hundreds of interacting 'qubits,' which are like tiny building blocks of information in quantum computers. These qubits were arranged in different shapes, such as squares and cubes. The problem was to understand how these qubits interact with each other, but this is extremely difficult to do on a classical computer.

The researchers used a technique called tensor networks to compress the information contained in the wave function of the quantum system. This made it possible to handle the calculations on an ordinary laptop. Joseph Tindall, an associate research scientist at the CCQ, compared the approach to 'a zip file for the wave function' that makes it easier to store and process.

The team's method can now be used to study more quantum dynamics problems and may also offer a strategy for optimization problems where researchers need to find the best solution among many possibilities. The findings were published in the journal Science.

Why It Matters

This breakthrough is important because it shows that ordinary computers, not just supercomputers, can solve complex quantum problems. This could lead to new discoveries and innovations in fields like materials science and technology.

Key Facts

  • Researchers at the Center for Computational Quantum Physics used an ordinary laptop to solve a difficult quantum problem.
  • The method uses advanced mathematics and specialized software to compress the information contained in the wave function of the quantum system.
  • The team's approach can now be used to study more quantum dynamics problems and may offer a strategy for optimization problems.
  • The findings were published in the journal Science on May 21, 2026.
  • The researchers used tensor networks to compress the information contained in the wave function.

Key Terms

qubits
Tiny building blocks of information in quantum computers that can exist in multiple states at once.
tensor networks
A mathematical technique used to compress and process large amounts of data, making it easier to handle complex calculations.

Implications

This breakthrough is important because it shows that ordinary computers, not just supercomputers, can solve complex quantum problems. This could lead to new discoveries and innovations in fields like materials science and technology.

Source: https://www.sciencedaily.com/releases/2026/07/260719040000.htm

Journal reference:

  1. Joseph Tindall, Antonio Francesco Mello, Matthew Fishman, E. Miles Stoudenmire, Dries Sels. Dynamics of disordered quantum systems with two- and three-dimensional tensor networks. Science, 2026; 392 (6800): 868 DOI: 10.1126/science.adx2728
  2. Andrew D. King, Alberto Nocera, Marek M. Rams, Jacek Dziarmaga, Roeland Wiersema, William Bernoudy, Jack Raymond, Nitin Kaushal, Niclas Heinsdorf, Richard Harris, Kelly Boothby, Fabio Altomare, Mohsen Asad, Andrew J. Berkley, Martin Boschnak, Kevin Chern, Holly Christiani, Samantha Cibere, Jake Connor, Martin H. Dehn, Rahul Deshpande, Sara Ejtemaee, Pau Farre, Kelsey Hamer, Emile Hoskinson, Shuiyuan Huang, Mark W. Johnson, Samuel Kortas, Eric Ladizinsky, Trevor Lanting, Tony Lai, Ryan Li, Allison J. R. MacDonald, Gaelen Marsden, Catherine C. McGeoch, Reza Molavi, Travis Oh, Richard Neufeld, Mana Norouzpour, Joel Pasvolsky, Patrick Poitras, Gabriel Poulin-Lamarre, Thomas Prescott, Mauricio Reis, Chris Rich, Mohammad Samani, Benjamin Sheldan, Anatoly Smirnov, Edward Sterpka, Berta Trullas Clavera, Nicholas Tsai, Mark Volkmann, Alexander M. Whiticar, Jed D. Whittaker, Warren Wilkinson, Jason Yao, T. J. Yi, Anders W. Sandvik, Gonzalo Alvarez, Roger G. Melko, Juan Carrasquilla, Marcel Franz, Mohammad H. Amin. Beyond-classical computation in quantum simulation. Science, 2025; 388 (6743): 199 DOI: 10.1126/science.ado6285

Leave a comment

← All research

Get Exclusive Insights with Every Issue

Join Shalyam Newsletter

Stay ahead in education, research, and innovation—straight to your inbox.