QEncode Benchmark
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water_dimer

/jordan wigner/uccsd tapered
Certified
Beats CCSD(T)
cc-pvdz

water_dimer_ccpvdz_JW_UCCSD_v4_tapered__sha256_6383f47170758daa

VQE Gap

1.9250e-6 Ha

CASCI ref

-152.062719 Ha

Qubits (tapered)

5

CCSD(T) corr.

-4.352e-1 Ha

Molecule / Problem

Namewater_dimer
Basis setcc-pvdz
GeometryO -1.551007 -0.114520 0.000000; H -1.934259 0.762503 0.000000; H -0.599677 0.040712 0.000000; O 1.350625 0.111469 0.000000; H 1.680398 -0.373741 -0.758561; H 1.680398 -0.373741 0.758561
Charge0
Spin0
Active electrons4
Active orbitals4
Orbital optimizationHF

Encoding / Circuit

Qubit mappingjordan-wigner
Ansatz typeuccsd_tapered
Ansatz reps (HEA)1
TaperingZ2 symmetry — 3 symmetries removed
Qubits (original)8
Qubits (tapered)5
Num parameters56
Circuit depth105
2Q gates20
Non-Clifford gates109
T gates (FT estimate)1,308 (ε = 0.001)

T-gate count is the resource-relevant cost of a fault-tolerant implementation. It is an estimate from the non-Clifford rotations in the pre-transpilation circuit, assuming standard rotation synthesis to precision ε — not a compiled count for a specific device.

Note on UCCSD circuit metrics

UCCSD uses exponential Pauli operators (exp(iθH)) that are symbolic before compilation. Circuit depth and 2-qubit gate counts are not reported here — they depend on the target hardware and transpiler.

Energy Results

HF energy-152.0625362496 Ha
MP2 energy-152.4734315200 Ha
CCSD energy-152.4912439611 Ha
CCSD(T) energy-152.4977225163 Ha
CASCI ground state-152.0627193590 Ha
VQE best energy-152.0627174339 Ha
|VQE − CASCI| gap1.925048e-6 Ha
CCSD(T) correlation-4.351863e-1 Ha

Optimizer / Run Config

AlgorithmCOBYLA
Multistart runs1
Max iterations500
Total func evals500
Num parameters56
Backenddefault.qubit

Provenance / Reproducibility

Entry IDwater_dimer_ccpvdz_JW_UCCSD_v4_tapered__sha256_6383f47170758daa
Schema version4.0.0
Created (UTC)2026-07-16T13:11:13.953680+00:00
SHA-256 hash6383f47170758daafe44c0a9ef50e7b794da0e5151b51662ec645c7583986195
Python3.11.15
PySCF2.6.2
PennyLane0.45.0
OpenFermion1.6.1
NumPy2.2.6
SciPy1.13.1

Reproduce this result

# Clone repo and install pinned environment

git clone https://github.com/qencode-benchmark/qencode-benchmark

cd qencode-benchmark

pip install -r requirements-v4.txt

# Run this entry

python scripts/generate_entry_v4.py \

--molecule water_dimer \

--mapping jordan_wigner \

--ansatz-type uccsd \

--multistart 1 \

--max-iter 500 \

--out-dir releases/v4/db