Skip to content
aiqbench takeQuantum Computing

aiqbench analysis

This study demonstrates the application of sample-based quantum diagonalization (SQD) to compute anharmonic vibrational spectra for polyyne chains, effectively managing the exponential growth of Hilbert space that hinders classical methods. By utilizing up to 104 qubits, the research highlights how quantum subspace techniques can capture spectroscopic details beyond full diagonalization limits, though it identifies multi-state recovery as a key scaling challenge.
Source coveringarXiv
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Sample-based quantum simulation of vibrational structure of polyyne chains

arXiv2 min read

arXiv:2610.09616v1 Announce Type: new Abstract: Predicting anharmonic vibrational spectra is a complex computational task, which becomes quickly infeasible as molecular size and the number of vibrational basis functions increase, leading to an exponential growth of the underlying Hilbert space. Here, we employ a sample-based quantum diagonalization (SQD) framework to compute anharmonic vibrational energies and spectra. The approach combines quantum state preparation and sampling with configuration recovery, diagonalization of the Hamiltonian projected in a subspace of basis configurations, and calculation of transition-dipole moments to obtain both vibrational energies and infrared spectra. We investigate two approaches for sampling, namely, vib-LUCJ and vib-SqDRIFT and apply the method to study the polyyne molecules C$_2$H$_2$ and C$_4$H$_2$, reaching representations requiring up to 104 qubits. Beyond energies, transition-dipole calculations reveal that infrared intensities and excited-state composition continue to evolve with basis size through anharmonic mixing and intensity redistribution, even when low-energy eigenvalues appear converged. These results show that sample-based quantum subspace methods can capture spectroscopic information in vibrational spaces far beyond the regime of full diagonalization. Moreover, our simulation identify multi-state recovery and scalable projected-space treatment as central challenges for further scaling sample-based approaches.

Abstract:Predicting anharmonic vibrational spectra is a complex computational task, which becomes quickly infeasible as molecular size and the number of vibrational basis functions increase, leading to an exponential growth of the underlying Hilbert space. Here, we employ a sample-based quantum diagonalization (SQD) framework to compute anharmonic vibrational energies and spectra. The approach combines quantum state preparation and sampling with configuration recovery, diagonalization of the Hamiltonian projected in a subspace of basis configurations, and calculation of transition-dipole moments to obtain both vibrational energies and infrared spectra. We investigate two approaches for sampling, namely, vib-LUCJ and vib-SqDRIFT and apply the method to study the polyyne molecules C$_2$H$_2$ and C$_4$H$_2$, reaching representations requiring up to 104 qubits. Beyond energies, transition-dipole calculations reveal that infrared intensities and excited-state composition continue to evolve with basis size through anharmonic mixing and intensity redistribution, even when low-energy eigenvalues appear converged. These results show that sample-based quantum subspace methods can capture spectroscopic information in vibrational spaces far beyond the regime of full diagonalization. Moreover, our simulation identify multi-state recovery and scalable projected-space treatment as central challenges for further scaling sample-based approaches.

arXiv:2610.09616 [quant-ph]

(or arXiv:2610.09616v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2610.09616 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Full text under the publisher's open licence · 274 words

Related coverage