25 Apr 2022
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4 minute read

Get ready for the IBM Quantum Spring Challenge

The IBM Quantum Spring Challenge kicks off Monday, May 23 at 9:00 a.m. U.S. Eastern Time. We invite participants to engage with cutting-edge research at the forefront of quantum simulation.

Get ready for the IBM Quantum Spring Challenge

The IBM Quantum Spring Challenge kicks off Monday, May 23 at 9:00 a.m. U.S. Eastern Time. We invite participants to engage with cutting-edge research at the forefront of quantum simulation.

More than A look back at the 40-year anniversary of the Physics of Computation Conference.four decades ago, theoretical physicist Richard Feynman said that in order to best simulate nature, your simulator needed to be quantum. Today, we’re working to develop machines that simulate nature — quantum computers — which have come a long way in the decades since. Simulating nature still remains one of the technology’s most promising applications, and the subject of some of the field’s most exciting, cutting-edge research.

This year, we’re celebrating that enduring legacy with the IBM Quantum Spring Challenge, which will center on the very same ideas that inspired Feynman’s comments in the first place. Nature simulations may be the first and perhaps most-widely studied of quantum computing applications, but they also continue to be a source of near-constant innovation in the field, and are helping us make our way toward tackling some of physics’ deepest mysteries. 

The IBM Quantum Spring Challenge runs from Monday, May 23 at 9:00 a.m. U.S. Eastern, until Friday, May 27 at 5:00 p.m. U.S. Eastern, and will cover two topics:

  • One will have participants tackle simulations of Read more about an efficient method to learn quantum many-body systems.many-body systems in condensed matter physics.
  • The other will tackle simulations of fermionic systems in chemistry.

Participants will get a one-of-a-kind opportunity to investigate problems at the forefront of quantum computing research.

It takes quantum to know quantum

Simulating nature is one of the few examples where quantum computing has clear application with a provable advantage. That’s because simulating the behaviors of multiple interacting quantum particles increases exponentially in complexity with each new variable that enters the picture. These systems quickly become too complex for even the most powerful classical supercomputers to simulate, but a quantum computer would be able to use phenomena like superposition and entanglement to tackle these problems much more efficiently.

Researchers have already been able to conduct important simulation experiments using the noisy quantum devices we have today. Just last year, a team of IBM Quantum and MIT researchers ran an experiment1 devising a novel approach to modeling particle transport and localization phenomena in many-body systems. Innovations like this and many others are setting the stage for a new era in the simulation of quantum-scale many-body systems. The IBM Quantum Spring Challenge is designed to give quantum researchers and enthusiasts a glimpse of what that future might look like. 

Experimenting with materials and many-body systems

So, what kinds of problems will Challenge participants be tackling? For one, we’ll attempt a quantum answer to an important question: “How do metals conduct electricity?”

From a classical physics lens, metals have free electrons that make it easy for electricity to flow through the atomic structure — we have Maxwell’s equations to describe this scenario. However, we can go even deeper.

From a quantum theory lens, we see that an atom’s electrons between discrete sites within a metal. These sites exist in close proximity to each other, and each one has the same energy level as its neighbors, which allows electrons to move easily between them. But things get a bit more complicated in real life.

Each of those sites — which we call “lattice sites” — actually have a slightly different energy level. These subtle differences that we observe across the entire lattice are distributed randomly. If the difference between the sites is substantial enough, an electron will bind to the site through a process known as Anderson localization,2 and will not move freely anymore. 

Challenge participants will start with a foundation of how to simulate these types of systems on a real quantum computer, and then expand to doing unique experiments to study how those electrons react under different circumstances. Participants will walk through the same initial steps that researchers use to better understand materials, and to one day help us create new kinds of materials.

Participants will try their hand at experimenting in areas that could potentially enable a vast array of useful applications.

Investigating chemistry simulations of fermionic systems — like water

In addition to helping us create new kinds of materials, quantum computers can also help us design better chemical reactions — which, in turn, could lead to groundbreaking advances in areas like agriculture, energy storage, and healthcare, to name just a few. 

In the Read the IBM Institute for Business Value’s quantum computing use cases for healthcare.healthcare sector, for example, pharmaceutical companies spend billions of dollars annually developing new, potentially lifesaving drugs. However, there’s a lot more that goes into drug discovery beyond simply identifying a molecule that can help treat or even cure an illness. Researchers also have to figure out how to synthesize large quantities of that molecule while minimizing the impurities that emerge as unintended results.

A better understanding of exactly what happens during chemical reactions could help us avoid or minimize these harmful side products and make chemical reactions more efficient. We study these via the behavior of their electrons, but simulating all of the electrons and their electron orbitals, that is, the spaces they occupy around the atomic nuclei, can be computationally costly. Thankfully, we can use a cutting-edge quantum simulation technique called “active space construction” to simulate only those orbitals used in the reaction, while a classical computer takes care of simulating the rest. 

Active space construction requires knowledge of several advanced concepts in computational chemistry. These include things like orbitals, basis sets, Hartree-Fock calculations, and the Learn how to simulate molecules using VQE in this Qiskit textbook tutorial.variational quantum eigensolver (VQE) algorithm — a workhorse of quantum computational chemistry. Participants in this year’s IBM Quantum Challenge will learn all about those concepts while refining the intuition required for effective active space construction, and will combine their knowledge and intuition to simulate their very own water molecule. 

Are you up for the challenge? 

We aren’t expecting participants to solve the mysteries of the universe in a week. (But we encourage you to try!) Instead, the challenge will guide you through what are essentially all the first steps a researcher would take in their effort to get some insight into concepts that are not currently well understood in the field of quantum computing.

Participants will also try their hand at experimenting in areas that could potentially enable a vast array of useful applications. They could help develop techniques that give researchers a better understanding of how to design lifesaving drugs and sustainable new materials, and help scientists answer fundamental questions about quantum mechanics that have plagued them for decades. 

If you’re excited about the power and potential of quantum simulation, we encourage you to get started by signing up for the IBM Quantum Spring Challenge, today. 

Date

25 Apr 2022

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Notes

  1. Note 1A look back at the 40-year anniversary of the Physics of Computation Conference. ↩︎
  2. Note 2Read more about an efficient method to learn quantum many-body systems. ↩︎
  3. Note 3Read the IBM Institute for Business Value’s quantum computing use cases for healthcare. ↩︎
  4. Note 4Learn how to simulate molecules using VQE in this Qiskit textbook tutorial. ↩︎

References

  1. Karamlou, A.H., Braumüller, J., Yanay, Y. et al. Quantum transport and localization in 1d and 2d tight-binding lattices. npj Quantum Inf 8, 35 (2022).
  2. Guan, C. Guan, X. A brief introduction to Anderson Localization. MIT. May 18, 2019