activity
20242026
collaborators

9 papers

physics.chem-ph2026

Analytical Nuclear Gradients and Hessians on Quantum Hardware via Orbital-Optimized VQE with Error Mitigation

Renato Olarte Hernandez, Karl Michael Ziems, Erik Kjellgren +3

Nuclear gradients and Hessians are fundamental quantities in computational chemistry, essential for a wide range of applications including geometry optimization, vibrational spectr…

quant-ph2026

Quantum error mitigation using energy sampling and extrapolation enhanced Clifford data regression

Zhongqi Zhao, Erik Rosendahl Kjellgren, Sonia Coriani +3

Error mitigation is essential for the practical implementation of quantum algorithms on noisy intermediate-scale quantum (NISQ) devices. This work explores and extends Clifford Dat…

quant-ph2025

Cost-effective scalable quantum error mitigation for tiled Ansätze

Oskar Graulund Lentz Rasmussen, Erik Kjellgren, Peter Reinholdt +4

We introduce a cost-effective quantum error mitigation technique that builds upon the recent Ansatz-based gate and readout error mitigation method (M0). The technique, tiled M0, le…

physics.chem-ph2025

Reduced density matrix and cumulant approximations of quantum linear response

Theo Juncker von Buchwald, Erik Rosendahl Kjellgren, Jacob Kongsted +3

Linear response (LR) is an important tool in the computational chemist's toolbox. It is therefore no surprise that the emergence of quantum computers has led to a quantum version,…

quant-ph2025

Hyperfine Coupling Constants on Quantum Computers: Performance, Errors, and Future Prospects

Phillip W. K. Jensen, Gustav Stausbøll Hedemark, Karl Michael Ziems +6

We present the first implementation and computation of electron spin resonance isotropic hyperfine coupling constants (HFCs) on quantum hardware. As illustrative test cases, we com…

physics.chem-ph2025

Critical Limitations in Quantum-Selected Configuration Interaction Methods

Peter Reinholdt, Karl Michael Ziems, Erik Rosendahl Kjellgren +3

Quantum Selected Configuration Interaction (QSCI) methods (also known as Sample-based Quantum Diagonalization, SQD) have emerged as promising near-term approaches to solving the el…