Quantum computing in materials and molecular sciences

Condensed matter theory makes a junction between the N-body problem, materials science and new questions raised by ever improving experiments. In particular, the response of matter excited by radiation such as light is often dominated by many-body effects, implying that the response of all electrons or nuclei cannot be understood as the sum of individual responses, not even qualitatively. The quantum nature of electrons constitutes an additional difficulty and source of surprises. Different strategies exist to deal with this problem at least approximately. These range from clever reformulations, for example in terms of functionals, to the use of model systems that can be studied over wide parameter ranges, and progress is based on advances of theory, algorithms, and new computational paradigms. In this talk, Dr Reining will explore some current challenges in excited states and spectroscopy of materials that push today’s approaches to their limits, and will open a discussion about bottlenecks in the various strategies that quantum computing could potentially overcome.

Dr Lucia Reining

French National Centre for Scientific Research (CNRS), France

Dr Lucia Reining

French National Centre for Scientific Research (CNRS), France

Lucia Reining is CNRS senior scientist at École Polytechnique, France. She studies condensed matter theory to understand and predict the response of matter excited by radiation such as light. This response is often dominated by “N-body” effects, implying that the response of all electrons is not the sum of individual responses. She has been one of the pioneers in including the electron-hole interaction in optical spectra calculations, going beyond existing semi-empirical approaches. In an ongoing dialogue between theory and experiment, she has proposed innovative, unified approaches to the N-body problem, while transforming these abstract formalisms into concrete tools for calculating the properties of everyday materials.

Of German origin, she obtained her PhD in Rome, before moving to the Centre Européen de Calcul Atomique et Moléculaire in the Paris region and then joining the CNRS. She is a founding member of the European Theoretical Spectroscopy Facility. She promotes an open, international and collaborative environment and diversity in research.

Biomolecular simulations are characterised by their enormous computational expense. They aim to provide dynamic information from the statis structures obtained experimentally, for example from X-ray crystallography, or cryo-electron microscopy, using physics-based models. Both quantum chemical calculations and classical molecular mechanics are required to understand biomolecular function, depending on the problem to be addressed. Quantum chemical calculations are needed to understand processes such as enzyme catalysis where covalent bonds are broken and reformed. Classical molecular dynamics (MD) simulations are used to explore protein and nucleic acid conformational ensembles where the covalent chemical structure remains fixed. Even with the most powerful supercomputer available (the Anton supercomputer), classical MD simulations of biomolecules are limited to milliseconds for individual protein structures containing around 1 million atoms. A simulation of a whole cell over timescales sufficient to observe cell division in atomistic detail would be computationally intractable.

These challenges raise the question of whether simulations that are currently impossible might become feasible on a quantum computer. Certainly, the ability to simulate quantum chemistry processes more efficiently could be a major breakthrough. Moreover, a quantum fast Fourier transform could also massively speed up the calculation of electrostatic interactions in biomolecules, which is a major bottleneck. Less established ideas include quantum evolution of conformational ensembles to determine free energies, and the use of quantum noise to improve sampling. The major challenge to the development of quantum algorithms is the enormous gap in language and expertise between the researchers developing quantum computation and the experts in the areas that quantum algorithms aim to address. Without this mutual understanding it is unlikely that quantum algorithms will be applicable to real problems.

Professor Sarah Harris

University of Sheffield, UK

Professor Sarah Harris

University of Sheffield, UK

Sarah Anne Harris (SAH) is a computational biophysicist and Chair of Biological and Materials Physics in the School of Mathematical and Physical Sciences in Sheffield. Her research uses high performance computer simulations to provide physical insight into biological mechanisms from the atomistic up to the cellular level. She has developed new theoretical physics tool to understand molecular biology at the mesoscale (https://ffea.bitbucket.io/), with a focus on modelling molecular motors such as dynein and myosin. Sarah is a strong advocate for the use of computation in the biological sciences, and is the current Chair of the Collaborative Computational Project in Biomolecular simulation (CCPBioSim) which supports UK researchers using simulations to understand biomolecular interactions and processes. CCPBioSim provides both beginners and experts workshops, and meetings identifying new cutting edge topics (https://www.ccpbiosim.ac.uk/).

The materials discovery landscape is undergoing a profound transformation driven by advances in multi-scale modelling approaches that connect atomic-level phenomena to real-world performance. This presentation examines the challenges and opportunities in integrating computational methods across different length and time scales to accelerate materials innovation. We highlight how modern computational approaches are evolving beyond isolated simulations to provide comprehensive frameworks that capture the complexity of real-world materials behaviour, from electronic structure to macroscopic properties. The presentation discusses how artificial intelligence and quantum computing can be strategically integrated with classical methods to overcome current computational bottlenecks and enhance predictive capabilities. Through detailed case studies in three high-impact domains—carbon capture technologies, pharmaceutical development, and corrosion-resistant materials—we demonstrate how multi-scale modelling approaches are solving previously intractable challenges and opening new pathways for innovation. As quantum computing technology matures, we emphasise the critical importance of developing robust integration infrastructure and middleware solutions that effectively connect quantum capabilities with established classical systems to deliver practical business value. This presentation argues that the future of materials discovery depends not on revolutionary advances in any single computational technique, but on our ability to seamlessly integrate complementary approaches across multiple scales, ultimately transforming how we discover, optimise, and deploy advanced materials for society's most pressing challenges.

Dr Phalgun Lolur

Capgemini Quantum Lab, UK

Dr Phalgun Lolur

Capgemini Quantum Lab, UK

Phalgun Lolur serves as the Scientific Quantum Development Lead at Capgemini Engineering, where he spearheads technical development initiatives at the intersection of quantum chemistry, materials science, data-driven methods, and quantum computing. Endorsed by the Royal Society for his expertise in theoretical and computational chemistry, quantum chemistry and computing, Dr Lolur brings over 15 years of experience in quantum simulations, optimisation, and machine learning applications.

In his role, Dr Lolur leads multidisciplinary teams across geographies to develop innovative solutions for complex challenges in the life sciences, consumer products, chemicals, and energy sectors. He is particularly focused on integrating quantum computing capabilities with existing classical methodologies to create comprehensive multi-scale modelling frameworks that bridge the gap between atomic-level simulations and real-world applications.

He is passionate about developing practical quantum computing applications that deliver tangible value by addressing some of the most challenging problems in chemistry and materials science. His expertise in translating cutting-edge quantum technologies into practical solutions positions him at the forefront of efforts to harness quantum computing's potential for accelerating materials innovation and scientific discovery.

Density Functional Theory (DFT) struggles with electronic structure problems involving strongly-correlated electrons, a domain where quantum computing holds a significant long-term advantage. To address this, the SIESTA-QCOMP project is developing a software package to embed quantum computing methodologies within classical DFT calculations performed with SIESTA. This hybrid approach aims to overcome the limitations of DFT for large-scale simulations of molecules and periodic systems containing strongly-correlated electrons.

SIESTA-QCOMP features a modular architecture with a driver program controlling the communication between the classical SIESTA code and quantum modules, primarily built on Qiskit. The current implementation utilises a VQE-based projection-embedding technique, with plans to incorporate SQD-based methods to extend the reach towards the quantum utility regime. Key challenges being addressed include adapting the classical code for a hybrid workflow, defining reliable embedding schemes, ensuring robust communication, and merging the quantum and classical results into a cohesive solution.

In the near future, the project will demonstrate this powerful approach by simulating an iron porphyrin molecule within a haemoglobin environment. This work not only provides a powerful new too for the SIESTA community but also establishes the foundation for a broader, long-term initiative, QCOMP4DFT, focused on ensuring interoperability between various DFT codes and quantum computing platforms.

Dr Yann Pouillon

CIC nanoGUNE, Spain

Dr Yann Pouillon

CIC nanoGUNE, Spain

After a French master's degree in Engineering from the École Nationale Supérieure de Physique de Strasbourg, France, and a PhD in Condensed Matter Physics from the University of Strasbourg, Yann has successively worked in Italy (2002 - 2003), Belgium (2003 - 2006), and Spain (2006 - present). He has been involved in multidisciplinary projects ranging from cutting-edge physics theory development to gas-sensor modelling and virtual reality visualisation of molecules, in close contact with experimentalists on many occasions, eg for the development of mechanically interlocked carbon nanotubes. More recently, Yann was lead software engineer and innovation architect at the Simune Atomistics startup, in San Sebastián, Spain, before joining its mother institution, CIC nanoGUNE, to have existing classical software packages leverage the upcoming Basque quantum computer.

With over 25 years of experience in scientific software development and 15 years of agile practices, Yann has helped various researchers and groups bring their software to higher quality standards and organise collaborative efforts for codes like ABINIT and SIESTA. He coordinated the software activities of the European Theoretical Spectroscopy Facility (ETSF) from 2008 to 2014, and was involved in designing its software repository and continuous integration infrastructure. He has maintained the nanoscale-physics metapackage in the Debian GNU/Linux distribution, co-created several data standards and their implementations, and actively participated in the deployment of libraries like LibXC. He has been one of the core developers of the CECAM Electronic Structure Library since its creation in 2014.

Further breakthroughs in materials for energy-related technologies such as lithium batteries and solar cells require advances in new compositions and underpinning materials science. Indeed, a greater fundamental understanding and optimisation of energy materials require nano-scale characterisation of their structural, ion transport and interface behaviour. In this context, atomistic modelling has been a powerful approach for investigating these properties, which have relied on advances in high end supercomputers. This presentation will describe such studies in two principal areas with an outline of what quantum computing can contribute to this field; (i) new high energy density cathode materials for lithium-ion EV batteries; (ii) halide perovskite materials for next-generation solar cells and optoelectronics.

Professor Saiful Islam

University of Oxford, UK

Professor Saiful Islam

University of Oxford, UK

Saiful is Professor of Materials Science at the University of Oxford. He grew up in Crouch End, north London, and obtained his Chemistry degree and PhD from University College London. He then worked at the Eastman Kodak Labs, New York, and the Universities of Surrey and Bath.

His research focuses on understanding atomic-scale processes in new materials for lithium batteries, sodium batteries and perovskite solar cells. Saiful has received several awards including the 2025 RSC Environment Prize, 2022 Royal Society Hughes Medal and 2020 ACS Storch Award in Energy Chemistry.

He presented the 2016 Royal Institution Christmas Lectures on BBC TV, which included a lemon battery world record. He is a Patron of Humanists UK and when not exploring new materials, he enjoys family breaks (as a dad of two), films and indie music.

Neutral atoms have emerged as a powerful and scalable platform for quantum computing, offering the ability to generate large numbers of identical and high quality qubits in reconfigurable arrays. By coupling atom to highly excited Rydberg states with strong, long-range dipole-dipole interactions it is possible to perform high-fidelity two and multi-qubit gate operations, or to natively implement classical graph optimisation problems, highlighting the versatility for performing both analogue and digital quantum computing.

In this talk we will present work at Strathclyde focused on developing large-scale system for quantum computing and optimisation, including demonstration of high fidelity single qubit gate operations on up to 225 qubits with errors below the threshold for fault tolerance using a non-destructive readout technique, as well as initial results from performing weighted graph optimisation using programmable local light-shifts across the atomy array. This provides a route to embedding a wider class of problems including quadratic unconstrained binary optimisation (QuBO) and integer factorisation, and extension to native implementations of graph colouring.

Alongside progress towards large-scale analogue optimisation, we will present a new cryogenic dual-species setup targeting fault-tolerant digital computation using quantum error-correction. This approach offers suppression of mid-circuit readout errors due to use of atoms of different species, and will provide a versatile test-bed for prototyping and benchmarking performance and scalability of recently proposed quantum low-density parity check codes.

Professor Jonathan Pritchard

University of Strathclyde, UK

Professor Jonathan Pritchard

University of Strathclyde, UK

Professor John Pritchard is an RAEng Senior Research Fellow and Head of Experimental Quantum Optics and Photonics Group at Strathclyde who is leading work developing neutral atom quantum computing. Through leadership of SQuAre, an EPSRC Prosperity Partnership with M Squared Lasers, his team have developed the UK's first scalable platform for neutral atom quantum computing, including developing new protocols for high fidelity multi-qubit gates and demonstrating single-qubit gate operations below the threshold fore fault tolerance on arrays of up to 225 qubits. This has enabled first demonstrations of optimisation on weighted graphs, and provides the underpinning technology for Maxwell, a commercial neutral atom platform developed by M Squared Lasers. As part of a new RAEng Fellowship he is now working to explore routes to fault-tolerant quantum computing be developing a cryogenic dual-species platform for implementing quantum error correction.

We discuss computational frameworks to carry out electronic structure calculations of solids on noisy intermediate scale quantum computers [1,2] using embedding theories [3], and we give examples for a specific class of materials, i.e., spin defects in solids. These are promising systems to build future quantum technologies, e.g., computers, sensors and devices for quantum communications. We also present a hybrid quantum- classical quantum monte carlo algorithm (QC-QMC) scheme [4] applied to both spin-defects in solids and molecules, which removes a pre-existing classical exponential bottleneck in post-processing; we show from experiments on quantum hardware that the QC-QMC algorithm is inherently noise robust. Although quantum simulations on quantum architectures are in their infancy and still face considerable challenges, promising results appear to be within reach.

[1] Quantum simulations of Fermionic Hamiltonians with efficient encoding and ansatz schemes, Benchen Huang, Nan Sheng, Marco Govoni, and Giulia Galli, J. Chem. Theory Comput. 19, 1487–1498 (2023).

[2] Simulating the electronic structure of spin defects on quantum computers, Benchen Huang, Marco Govoni, and Giulia Galli, PRX Quantum 3, 010339 (2022).

[3] Quantum Embedding Theories to Simulate Condensed Systems on Quantum Computers, Christian Vorwerk*, Nan Sheng*, Marco Govoni, Benchen Huang, and Giulia Galli Nat. Comput. Sci. 2, 424 (2022).

[4] Evaluating a quantum-classical quantum Monte Carlo algorithm with Matchgate shadows, Benchen Huang, Yi-Ting Chen, Brajesh Gupt, Martin Suchara, Anh Tran, Sam McArdle, and Giulia Galli, Phys. Rev. Research 6, 043063 (2024).

Professor Giulia Galli

University of Chicago, USA

Professor Giulia Galli

University of Chicago, USA

Giulia Galli is the Liew Family Professor of Electronic Structure and Simulations in the Pritzker School of Molecular Engineering and the Department of Chemistry at the University of Chicago, and a Senior Scientist at Argonne National Laboratory, where she is the director of the Midwest Integrated Center for Computational Materials. She is an expert in the development of theoretical and computational methods for the study of material and molecular properties using quantum simulations. She is a member of the US National Academy of Sciences, the American Academy of Arts and Science, and the International Academy of Quantum Molecular Science, and a Fellow of the American Association for the Advancement of Science and of the American Physical Society. She is the recipients of numerous awards in computational physics, theoretical chemistry, materials science and nanoscience.