QEX - Quantum-Enhanced Density Functional Theory in JAX
JAX-based differentiable Kohn-Sham DFT implementation for training quantum-enhanced neural exchange-correlation functionals
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portfolio
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publications
Quantum algorithms for electronic structure calculations: particle/hole Hamiltonian and optimized wavefunction expansions
Published in Physical Review A, 2018
A quantum algorithm for electronic structure based on transforming the Hamiltonian into the particle-hole representation for more compact Ansatz.
Recommended citation: Panagiotis Kl. Barkoutsos, Igor O. Sokolov, et al. (2018). "Quantum algorithms for electronic structure calculations: particle/hole Hamiltonian and optimized wavefunction expansions." Phys. Rev. A
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Quantum algorithm for alchemical optimization in material design
Published in Chemical Science, 2020
A quantum algorithm to efficiently explore chemical compound space for material and drug design by leveraging alchemical Hamiltonians.
Recommended citation: Panagiotis Kl. Barkoutsos, Igor O. Sokolov, et al. (2020). "Quantum algorithm for alchemical optimization in material design." Chem. Sci.
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Quantum orbital-optimized unitary coupled cluster methods in the strongly correlated regime: Can quantum algorithms outperform their classical equivalents?
Published in Journal of Chemical Physics, 2020
Evaluation of efficient variants of quantum Unitary Coupled Cluster Ansatz with orbital optimization to tackle strongly correlated electronic systems.
Recommended citation: Igor O. Sokolov, et al. (2020). "Quantum orbital-optimized unitary coupled cluster methods in the strongly correlated regime." J. Chem. Phys.
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Microcanonical and finite-temperature ab initio molecular dynamics simulations on quantum computers
Published in Physical Review Research, 2021
Demonstration of variational quantum algorithms for computing atomic forces for ab initio molecular dynamics simulations, validated on IBM quantum hardware.
Recommended citation: Igor O. Sokolov, et al. (2021). "Microcanonical and finite-temperature ab initio molecular dynamics simulations on quantum computers." Phys. Rev. Research
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Orders of magnitude reduction in the computational overhead for quantum many-body problems on quantum computers via an exact transcorrelated method
Published in Physical Review Research, 2022
Extension of transcorrelated methods to quantum simulation, achieving up to four orders of magnitude improvement in accuracy while using shallower circuits.
Recommended citation: Igor O. Sokolov, et al. (2022). "Orders of magnitude reduction in the computational overhead for quantum many-body problems on quantum computers via an exact transcorrelated method." Phys. Rev. Research
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Enhancing Graph Neural Networks with Quantum Computed Encodings
Published in ICML 2024, 2023
Novel positional encodings for graph transformers inspired by quantum systems, published at ICML 2024.
Recommended citation: Slimane Thabet, Igor O. Sokolov, et al. (2023). "Enhancing Graph Neural Networks with Quantum Computed Encodings." ICML 2024
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Quantum-enhanced Neural Exchange-Correlation Functionals
Published in arXiv (Top 3 Best Papers at MoML 2024 at MIT), 2024
We introduced a differentiable Kohn-Sham DFT framework using quantum neural networks to learn exchange-correlation functionals, achieving chemical accuracy on molecular systems.
Recommended citation: Igor O. Sokolov, et al. (2024). "Quantum-enhanced Neural Exchange-Correlation Functionals." arXiv:2404.14258
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Ab Initio Transcorrelated Method enabling accurate Quantum Chemistry on near-term Quantum Hardware
Published in Journal of Chemical Theory and Computation (JCTC), 2024
A noise-resilient quantum algorithm for electronic structure based on exact transcorrelated approach, yielding chemically accurate dissociation energies with 4-6 qubits.
Recommended citation: Igor O. Sokolov (shared first authorship), et al. (2024). "Ab Initio Transcorrelated Method enabling accurate Quantum Chemistry on near-term Quantum Hardware." JCTC
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Hardware-Tailored Diagonalization Circuits
Published in npj Quantum Information, 2024
A theoretical framework for constructing hardware-tailored quantum circuits that efficiently diagonalize sets of commuting Pauli operators with minimal gate overhead.
Recommended citation: Daniel Miller, Igor O. Sokolov, et al. (2024). "Hardware-Tailored Diagonalization Circuits." npj Quantum Inf.
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talks
Quantum Algorithms for Chemistry
Published:
Won the Best Talk Award at the QCxQC Conference. Watch the talk on YouTube.
Quantum Machine Learning for Chemistry
Published:
Tutorial on quantum machine learning approaches for chemistry applications at the Kyiv Academic University quantum ML school.
Enhancing Graph Neural Networks with Quantum Computed Encodings
Published:
Poster presentation at the International Conference on Machine Learning (ICML 2024), a top-tier AI conference. Presented our work on quantum-inspired positional encodings for graph transformers.
Quantum-enhanced Neural Exchange-Correlation Functionals
Published:
Nominated for Top 3 Best Papers award. Presented our work on differentiable Kohn-Sham DFT framework using quantum neural networks to learn exchange-correlation functionals.
teaching
IBM Quantum Challenge 2021 - Chemistry Exercise
Online Challenge, IBM Quantum, 2021
Lead developer for the chemistry challenge in IBM Quantum Challenge 2021. Designed educational exercises teaching participants about quantum algorithms for chemistry, including variational quantum eigensolvers and molecular simulations.
Student Supervision at Pasqal and IBM
Research Supervision, Pasqal & IBM Research, 2023
Supervised MSc and PhD students at both IBM Research Zurich and Pasqal on topics including:
- Quantum algorithms for electronic structure
- Variational quantum eigensolvers
- Quantum machine learning for chemistry
- Transcorrelated methods for quantum simulation