Quantum Simulation
How Quantum Computers Are Addressing Some of Our Toughest Challenges Virtually
Years ago, I enjoyed the sensation of flying aircraft on the Microsoft Flight Simulator. My first exposure was Flight Simulator 2.0 after its release in 1984. Some may remember at the time it being an incredible advance yet compared with Flight Simulator 2020, it was frankly rudimentary. Still, that is software evolution for you.
Regardless of the quality of the software, what Flight Simulator offered was a chance to experience something that occurs in the real world from your desktop or laptop. Each simulation incorporated factors like wind speed, wind direction, air speed, plane configuration, amount of flaps, remaining fuel, visibility and the list goes on.
No different are simulations to solve the world’s biggest problems today like chemical combinations for fertilizer, development of recyclable materials, protein modelling for new vaccine solutions, innovations in human tissue replacement, superconductivity at room temperature and room pressure and more. Yet the challenge for scientists and researchers arises in the multitude of possible combinations resident in the Periodic Table of Elements (PTE). The PTE of metals, minerals and gases is arranged by atomic number, electron configuration, and recurring chemical properties, with 94 occurring naturally and 24 synthesized in labs.
Attempting to list all the combinations is one thing. Attempting to analyse the reactions of interactions of these combinations is quite another. The complexity of combinations and computations is almost infinite. Far beyond the capabilities of classical computing. Which is where quantum simulation enters the fray.
What’s a simulation? A simulation is imitating a real-world system or process over a period of time. Starting with a model, which represents the dominant behaviours or characteristics the selected system or process, the simulation illustrates the evolution of the model over time.
Quantum Simulation
Quantum simulation is one of the most promising routes to discovering new materials with new properties. For example, in the field of condensed matter physics which looks at the properties of solids and liquids and their atomic configuration, quantum simulation holds great promise. Certainly, the search for novel materials continues (no one can categorically state we have found them all), and the search incorporates many properties like:
· Strength
· Resistance to heat or cold
· Thickness
· Magnetism
· Electronics
· Interaction with light
· Permeability
And many more.
Take superconductivity for example. Superconductivity is important in things like magnetic resonance imaging (MRI) magnets and particle accelerators. Aluminum’s properties allow for electricity to flow through the material with zero resistance when cooled to 1.75 Kelvin. The challenge is cooling it to 1.75K outside of the lab. So, quantum simulation could be used to search for combinations of elements that permit superconductivity at room temperature, and to do the search much faster than a traditional computer.
Simulations almost must consider the chemistry aspect of combining elements together (such as the risk of a dangerous reaction in testing), so again quantum simulators could address the simulation of these interactions. Any errors, even infinitesimally small errors in the computation by classical computers, could lead to errors in the rate of chemical reaction and precision of interactions between electrons and atoms.
Progress Towards Quantum Simulation
In 2019, IonQ simulated water (H20) molecules “with accuracy approaching what is needed for practical applications in the promising field of computational chemistry”. In previous years, Google simulated hydrogen (2016) and IBM simulated lithium hydride and beryllium hydride (2017). D-Wave Systems Inc. recently announced their “Fully-programmable annealing quantum computer demonstrates 3 million times speed-up over classical CPU in a practical application” for a simulation of exotic magnetism. So, as one can see, there are existing precedents for simulating molecules/atoms today that offer hope for additional discoveries.
In terms of quantum computing hardware progress, IBM’s recent roadmap announcement suggested they would be processing at over 1000 qubits by 2023. Both IBM and Google forecast over 1 million error-corrected qubits processing capability by 2030. These are phenomenal numbers compared to today’s quantum computer capabilities (in the tens and hundreds), and are only some of the types of quantum technology available today.
Barriers to Quantum Simulation
In today’s quantum computing reality, there are several barriers to the effective and efficient computational simulation of elements including:
· Implementing quantum error correction at scale
· Achieving these error-corrected qubit levels of quantum processing
· Discovering how to route wiring for 1 million qubits
· Leveraging simulations across all hardware platforms (superconducting, annealing, ion trap, photonics and any new approaches)
· Talent to run simulations
· Room temperature processing (seeing progress with photonic computers here)
· And many more
Conclusion
Yet when have barriers stopped humanity from the voyage of discovery? Quantum simulation appears inevitable and researchers and pioneers are pushing the edges of innovation to develop new materials and more importantly new solutions to support our own voyages of discovery. The exciting journey of those in the quantum computing field has really just begun. Better, faster, more accurate processors along with more experienced simulation talent and challenging problems to solve are a combination not unlike our forebears with better ships, more experienced crew and undiscovered seas to reach.
Copyright 2021 Aquitaine Innovation Advisors
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Brian Lenahan is the author of four Amazon-published books on artificial intelligence including the Bestseller “Artificial Intelligence: Foundations for Business Leaders and Consultants”. He is a former executive in a Top 10 North American bank, a University Instructor, and mentors innovative companies in the Halton and Hamilton areas. Brian’s training in AI comes from MIT and he writes extensively on artificial intelligence and quantum computing strategy.
Email: ceo@aquitaineinnovationadvisors.com
LinkedIn: https://www.linkedin.com/in/brian-lenahan-innovation/
Aquitaine Innovation Advisors: www.aquitaineinnovationadvisors.com
To find out more about Quantum London go to LinkedIn or contact Paolo Cuomo or Emanuele Colonnella on Medium.
