Basis Adaptive Algorithm for Quantum Many-Body Systems on Quantum Computers
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866915674877591552 |
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| author | Biswas, Anutosh Ghosh, Sayan Majumdar, Ritajit Rahaman, Mostafizur Kumar, Manoranjan |
| author_facet | Biswas, Anutosh Ghosh, Sayan Majumdar, Ritajit Rahaman, Mostafizur Kumar, Manoranjan |
| contents | A new basis adaptive algorithm for hybrid quantum-classical platforms is introduced to efficiently find the ground-state (gs) properties of quantum many-body systems. The method addresses limitations of many algorithms, such as Variational Quantum Eigensolver (VQE) and Quantum Phase Estimation (QPE) etc by using shallow Trotterized circuits for short real-time evolution on a quantum processor. The sampled basis is then symmetry-filtered by using various symmetries of the Hamiltonian which is then classically diagonalized in the reduced Hilbert space. We benchmark this approach on the spin-1/2 XXZ chain up to 24 qubits using the IBM Heron processor. The algorithm achieves sub-percent accuracy in ground-state energies across various anisotropy regimes. Crucially, it outperforms the Sampling Krylov Quantum Diagonalization (SKQD) method, demonstrating a substantially lower energy error for comparable reduced-space dimensions. This work validates symmetry-filtered, real-time sampling as a robust and efficient path for studying correlated quantum systems on current near-term hardware. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_12753 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Basis Adaptive Algorithm for Quantum Many-Body Systems on Quantum Computers Biswas, Anutosh Ghosh, Sayan Majumdar, Ritajit Rahaman, Mostafizur Kumar, Manoranjan Strongly Correlated Electrons Quantum Physics A new basis adaptive algorithm for hybrid quantum-classical platforms is introduced to efficiently find the ground-state (gs) properties of quantum many-body systems. The method addresses limitations of many algorithms, such as Variational Quantum Eigensolver (VQE) and Quantum Phase Estimation (QPE) etc by using shallow Trotterized circuits for short real-time evolution on a quantum processor. The sampled basis is then symmetry-filtered by using various symmetries of the Hamiltonian which is then classically diagonalized in the reduced Hilbert space. We benchmark this approach on the spin-1/2 XXZ chain up to 24 qubits using the IBM Heron processor. The algorithm achieves sub-percent accuracy in ground-state energies across various anisotropy regimes. Crucially, it outperforms the Sampling Krylov Quantum Diagonalization (SKQD) method, demonstrating a substantially lower energy error for comparable reduced-space dimensions. This work validates symmetry-filtered, real-time sampling as a robust and efficient path for studying correlated quantum systems on current near-term hardware. |
| title | Basis Adaptive Algorithm for Quantum Many-Body Systems on Quantum Computers |
| topic | Strongly Correlated Electrons Quantum Physics |
| url | https://arxiv.org/abs/2512.12753 |