Measure qubit transmission capacity, effective entropy flow, and corrected output rates today. Enter channel data. Get precise estimates, formulas, graphs, exports, examples, and guidance.
| Scenario | Qubit Rate | Channels | Fidelity | QBER | Entropy | Effective Information/Qubit | Final Rate (bps) |
|---|---|---|---|---|---|---|---|
| Short-range low-noise link | 600,000 | 1 | 0.980 | 0.010 | 1.000000 | 0.848310 | 449,688.88 |
| Satellite-assisted transfer | 1,800,000 | 3 | 0.920 | 0.040 | 0.995378 | 0.514306 | 1,787,995.06 |
| Lab fiber with correction overhead | 950,000 | 2 | 0.950 | 0.025 | 0.985815 | 0.661962 | 951,470.50 |
This calculator uses a practical engineering approximation for binary quantum sources and noisy transmission. It is useful for planning, comparison, and rate estimation.
H = -p0 log2(p0) - p1 log2(p1)
This measures how much information each prepared qubit can ideally carry when the source has probabilities p0 and p1.
h(q) = -q log2(q) - (1 - q) log2(1 - q)
This estimates the uncertainty introduced by the quantum bit error rate.
D = exp(-t / Td)
Here, t is transmission time and Td is decoherence time. Longer travel relative to coherence time reduces preserved information.
Ieff = max(0, H × Fidelity × D - h(q))
This adjusts source entropy for fidelity, decoherence, and noise.
Qeff = Qraw × Channel Efficiency × Coding Efficiency
Raw throughput equals qubit generation rate multiplied by parallel channels.
Rate = Qeff × Ieff
The final result is reported in bits per second, plus larger output intervals and spectral efficiency.
Quantum information rate tells you how much usable information survives through a real channel in one second. Raw qubit production alone is not enough. Noise, decoherence, imperfect fidelity, and coding overhead all reduce the useful output. A system can look fast on paper and still deliver a much lower corrected rate after realistic losses.
This calculator combines source entropy, error entropy, decoherence loss, channel efficiency, and coding efficiency into one practical output number. The source entropy term describes how much information is available before transmission. Fidelity and decoherence scale that ideal content downward. Error entropy subtracts uncertainty caused by bit errors. Effective throughput then applies transport and coding constraints to find a realistic final rate.
A higher final rate means more useful information is preserved each second. Compare the ideal rate with the adjusted rate to see the true cost of losses. The quality index helps summarize how much of the original information content remains after correction factors. The secure key estimate is also helpful for quantum communication studies, especially when exploring error sensitivity in key-distribution style channels.
Use this page for design studies, classroom demonstrations, laboratory planning, and side-by-side channel comparisons. It is especially useful when you want one compact view of entropy, throughput, loss, and spectral efficiency. For full density-matrix simulation, you would need a more specialized model, but this tool gives a strong first-pass estimate for many planning tasks.
It estimates usable quantum information output per second after accounting for source entropy, fidelity, decoherence, error rate, transport efficiency, and coding losses.
They define the binary source distribution. Balanced probabilities produce higher entropy, while skewed probabilities lower the ideal information available per prepared qubit.
The calculator normalizes them automatically. This keeps the entropy calculation physically meaningful and prevents invalid source distributions from breaking the result.
Quantum bit error rate is the fraction of transmitted bits expected to be wrong. Higher QBER increases uncertainty and sharply reduces useful information.
Quantum states lose coherence over time. When transmission time becomes large relative to decoherence time, preserved information falls quickly and the final rate drops.
No. It is an advanced planning calculator that uses a practical approximation. It is ideal for comparison, sizing, and educational analysis.
It is the final information rate divided by bandwidth. This shows how effectively the channel turns available bandwidth into usable information output.
Yes. The secure key estimate gives a helpful secondary benchmark, especially when testing how noise and decoherence affect corrected secure throughput.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.