School of Materials Science and Engineering (MSE)

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1 to 10 of 7,950 Results

Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations. Apr 9, 2026 - Rafika RAHMAWATI Rahmawati, Rafika; Li, Shuzhou, 2026, "Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations.", https://doi.org/10.21979/N9/LDPUKT, DR-NTU (Data), V2 The provided data includes the general source code and its computational results.
Benchmark-1-UCCSD-Tier1-ipynb-09042026.ipynb Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations. Jupyter Notebook - 305.7 KB - MD5: 7efad5b4a45371e7b05eaf26fc37879e Benchmark VQE using UCCSD ansatz with Gradient Descent and Quantum Natural Gradient Optimizer
Benchmark-2-HE-Tier1-ipynb-09042026.ipynb Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations. Jupyter Notebook - 599.4 KB - MD5: f7601afba1cea436f8cf9ab71e3ecc8a Benchmark VQE using Hardware Efficient ansatz with Gradient Descent and Quantum Natural Gradient Optimizer
Benchmark-3-kUpCCGSD-Tier1-ipynb-09042026.ipynb Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations. Jupyter Notebook - 119.9 KB - MD5: 1ba8e13a293df80fb017384f82d11fd3 Benchmark VQE using kUpCCGSD ansatz with Gradient Descent and Quantum Natural Gradient Optimizer
Noiseless-comp-cost-Tier1-png-08042026 Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations. PNG Image - 215.3 KB - MD5: d2d913e58a411cf2e2a1cf75a966b23e Noiseless computation cost of min energy calculated using VQE
Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they? Nov 19, 2025 - Darrell Jun Jie TAY Tay, Darrell Jun Jie, 2025, "Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they?", https://doi.org/10.21979/N9/HBVMXK, DR-NTU (Data), V1, UNF:6:/L/2QMEJnyiRabOOgRwOoA== [fileUNF] Raw Data
01-DMA100-Fresh-top-5.jpg Nov 19, 2025 - Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they? JPEG Image - 642.2 KB - MD5: b5122c713021b2a8f2ba9ddfe8178e09
02-CsPbI3-Fresh-top-4.jpg Nov 19, 2025 - Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they? JPEG Image - 649.5 KB - MD5: 566bd2e5b056d5d0ac342d6acf7e1575
03-DMA150-Fresh-top-4.jpg Nov 19, 2025 - Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they? JPEG Image - 699.4 KB - MD5: 87020dc2662f278a904e12d5d74d213d
04-DMA100-125C1h-top-8.jpg Nov 19, 2025 - Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they? JPEG Image - 686.6 KB - MD5: 8a7ea6cf30f3cd366f4611a7915dc940

Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations.

Apr 9, 2026 - Rafika RAHMAWATI

Rahmawati, Rafika; Li, Shuzhou, 2026, "Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations.", https://doi.org/10.21979/N9/LDPUKT, DR-NTU (Data), V2

The provided data includes the general source code and its computational results.

Benchmark-1-UCCSD-Tier1-ipynb-09042026.ipynb

Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations.

Jupyter Notebook - 305.7 KB -

Benchmark VQE using UCCSD ansatz with Gradient Descent and Quantum Natural Gradient Optimizer

Benchmark-2-HE-Tier1-ipynb-09042026.ipynb

Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations.

Jupyter Notebook - 599.4 KB -

Benchmark VQE using Hardware Efficient ansatz with Gradient Descent and Quantum Natural Gradient Optimizer

Benchmark-3-kUpCCGSD-Tier1-ipynb-09042026.ipynb

Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations.

Jupyter Notebook - 119.9 KB -

Benchmark VQE using kUpCCGSD ansatz with Gradient Descent and Quantum Natural Gradient Optimizer

Noiseless-comp-cost-Tier1-png-08042026

Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations.

PNG Image - 215.3 KB -

Noiseless computation cost of min energy calculated using VQE

Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they?

Nov 19, 2025 - Darrell Jun Jie TAY

Tay, Darrell Jun Jie, 2025, "Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they?", https://doi.org/10.21979/N9/HBVMXK, DR-NTU (Data), V1, UNF:6:/L/2QMEJnyiRabOOgRwOoA== [fileUNF]

Raw Data

01-DMA100-Fresh-top-5.jpg

Nov 19, 2025 - Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they?

JPEG Image - 642.2 KB -

02-CsPbI3-Fresh-top-4.jpg

Nov 19, 2025 - Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they?

JPEG Image - 649.5 KB -

03-DMA150-Fresh-top-4.jpg

Nov 19, 2025 - Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they?

JPEG Image - 699.4 KB -

04-DMA100-125C1h-top-8.jpg

Nov 19, 2025 - Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they?

JPEG Image - 686.6 KB -

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