## Dr Nicole Holzmann

*Riverlane, Cambridge, United Kingdom *

Quantum computers have the potential to impact a wide range of industries [1] through their application to problems such as computational fluid dynamics, combinatorial optimisation and computational chemistry. Due to the quantum nature of fermions, the last of these looks to be a particularly promising application area – as Feynman put it in the early 80s, nature is quantum mechanical by default and thus its simulation requires a quantum computer.

Such calculations have relevance to the pharmaceutical and materials industries, presenting opportunities to revolutionise the Computer-Aided Drug Design process [2,3], and the development of battery materials and catalysts [4,5]. Initial studies on using quantum computers in such situations have been published by global industrial and quantum players [6-9].

Quantum computing capabilities are currently limited and they are unable to perform useful computational chemistry calculations. However, quantum hardware is advancing, with milestones being reached [10-12] and roadmaps being published [13,14]. At the same time, algorithm development had reduced the estimated quantum computational resources needed to run computational chemistry calculations [e.g. 15].

From the viewpoint of a computational chemist, in this talk we want to look at where the hype about quantum computing ends and where reality starts. How does a quantum computer work, what is a qubit and what are the problems and challenges of the technology? What can a quantum computer do for a chemist, when will we be able to actually do a useful quantum chemical calculation and what resources would we need? How can method and algorithm development help us to make quantum computing useful, sooner?

## Recording:

### References:

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[2] M Evers, A Heid, I Ostojic*, *** Pharma’s digital Rx: Quantum computing in drug research and development**, McKinsey & Company

**2021**https://www.mckinsey.com/industries/life-sciences/our-insights/pharmas-digital-rx-quantum-computing-in-drug-research-and-development

[3] M Langione, JF Bobier, C Meier, S Hasenfuss, U Schulze, ** Will Quantum Computing Transform Biopharma R&D?**, Boston Consulting Group

**2019**, https://www.bcg.com/fr-fr/publications/2019/quantum-computing-transform-biopharma-research-development

[4] F Budde, D Volz, *The next big thing? Quantum computing’s potential impact on chemicals**, *McKinsey & Company **2019**, https://www.mckinsey.com/industries/chemicals/our-insights/the-next-big-thing-quantum-computings-potential-impact-on-chemicals

[5] O Burkacky, N Mohr, L Pautasso, ** Will quantum computing drive the automotive future?**, McKinsey & Company

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*PNAS*

**2017**, 114(29), 7555-7560. https://doi.org/10.1073/pnas.1619152114

[7] V von Burg, G H Low, T Haner, DS Steiger, M Reiher, M Roetteler, M Troyer, ** Quantum computing enhanced computational catalysis**,

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**2021**, 3, 033055. https://doi.org/10.1103/PhysRevResearch.3.033055

[8] JE Rice, TP Gujarati, M Motta, TY Takeshita, E Lee, JA Latone, JM Garcia, ** Quantum computation of dominant products in lithium–sulfur batteries**,

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**2021**,

*154*, 134115. https://doi.org/10.1063/5.0044068

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**,**505. https://doi.org/10.1038/s41586-019-1666-5

[11] HS Zhong, H Wang, YH Deng, MC Chen, LC Peng, YH Luo, J Qin, D Wu, X Ding, Y Hu, P Hu, XY Yang, WJ Zhang, H Li, YX Li, X Jiang, L Gan, GW Yang, LX You, Z Wang, L Li, NL Liu, CY Lu, JW Pan, ** Quantum computational advantage using photons**,

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**2020,**

*370*(6523), 1460. DOI: 10.1126/science.abe8770

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**2021**https://siliconangle.com/2021/11/15/ibm-debuts-new-eagle-quantum-processor-127-qubits/

[13] J Gambetta, ** IBM’s roadmap for scaling quantum technology**, IBM

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[14] P Chapman, ** Scaling IonQ’s quantum computers: The roadmap**, IonQ

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[15] J Lee, DW Berry, C Gidney, WJ Huggins, JR McClean, N Wiebe, R Babbush, ** Even more efficient quantum computations of chemistry through tensor hypercontraction**,

*PRX Quantum*

**2021**, 2, 030305, https://doi.org/10.1103/PRXQuantum.2.030305