Jitter Calculation Tool

Inputs

Paste a series of periods or timestamps. Separate values with commas, spaces, or new lines.

Input mode

Timestamps are converted to periods internally.

Units

Use the unit of your samples.

Reference

Reference defines the “error” baseline.

Nominal period (optional for timestamps)

For periods, this is required.

Percentile (|error|)

Common values: 90, 95, 99.

Preview rows

Controls the preview table length.

Samples (periods or timestamps)

Tip: one value per line is easiest to audit.

Results appear above this form.

Example data table

These period samples represent a nominal 10.000 ns clock with small variation.

#	Period (ns)	Notes
1	10.10	Typical sample
2	9.92	Typical sample
3	10.05	Typical sample
4	10.22	Slightly long period
5	9.88	Short period
6	10.01	Typical sample
7	10.14	Slightly long period
8	9.95	Typical sample
9	10.07	Typical sample
10	9.99	Typical sample
11	10.11	Slightly long period
12	9.90	Short period

Formula used

Let P_i be each measured period and P_ref be the chosen reference period.

Period error (jitter sample)

e_i = P_i − P_ref

Positive error means the period is longer than reference.

RMS jitter (σ of error)

σ = sqrt( Σ(e_i − ē)² / (n−1) )

ē is the mean of e_i. Uses sample standard deviation.

Peak-to-peak jitter (error)

J_pp = max(e_i) − min(e_i)

Captures the full spread of measured error.

TIE from period errors

TIE_k = Σ_i=1..k e_i

In timestamp mode, TIE is computed versus an ideal clock.

Note

The “DJ proxy” shown is a quick comparison metric: DJ ≈ max(0, J_pp − 2σ). It is not a standards-based decomposition.

How to use this calculator

Choose an input mode. Use periods if you already have period measurements. Use timestamps if you logged edge times.
Set units. Pick the unit that matches your pasted numbers.
Pick a reference. Nominal uses your expected period. Mean removes DC offset in the error series.
Paste samples. Use commas or new lines. Provide at least three values.
Submit. Review RMS, peak-to-peak, percentile, and TIE. Export CSV or generate a PDF from the results section.

Timing Budgets

Jitter is the short term variation of edge timing around an expected schedule. In clocks, serial links, and packetized networks, small timing noise can consume a large fraction of a tight budget. For example, a 10.000 ns nominal period with 0.050 ns RMS error represents 0.5% timing uncertainty, which may reduce setup and hold margin. Measuring jitter across many samples helps separate stable behavior from occasional excursions.

Metric Interpretation

This tool reports RMS jitter as the standard deviation of period error, which aligns with random variation in many systems. Peak to peak jitter captures the full spread between the worst early and worst late samples, making it sensitive to outliers and rare events. Percentile absolute jitter, such as the 95th, is a robust alternative: it answers how large most errors are without letting one spike dominate the metric. It supports quick comparisons across benches and releases.

TIE Insights

Time Interval Error, or TIE, is the cumulative timing difference relative to an ideal clock. Even if periods look acceptable, small biases can accumulate and create large phase wander. In period mode, TIE is the running sum of period errors; in timestamp mode, it is computed directly against an ideal time grid. A wide TIE peak to peak value often indicates low frequency modulation, wander, or buffering effects.

Reference Choices

Reference selection changes what the tool calls error. Using a nominal period is best for compliance checks where a specification defines the target value. Using the mean period removes DC offset, which can highlight noise and cycle to cycle variation. Units should match the measurement source; mixing nanoseconds and microseconds can inflate results by 1000 times. When importing data, keep sampling conditions consistent, such as temperature, load, and link rate.

Reporting Practices

For validation, report sample count, reference choice, RMS, peak to peak, and a percentile value together. Pair the numeric summary with the preview table to spot patterns like alternating long and short periods or step changes. When troubleshooting, compare runs before and after a change, and watch whether RMS falls while peak to peak stays high, which can suggest intermittent interference. Exported CSV supports spreadsheets and lab notebooks.

FAQs

1) What input format does the tool accept?

Paste values separated by commas, spaces, semicolons, or new lines. Use period samples in the chosen unit, or timestamps when edges were logged. At least three values are required for stable statistics.

2) Should I use nominal or mean reference?

Nominal is best when verifying a specified target period. Mean is useful for comparing noise between runs because it removes constant offset. If your frequency is drifting slowly, nominal highlights that drift in the error series.

3) What does RMS jitter represent?

RMS jitter is the standard deviation of period error. It summarizes typical variation and is less dominated by single spikes than peak to peak. For roughly Gaussian noise, many samples fall within about two RMS values of zero.

4) Why is peak to peak jitter sometimes large?

Peak to peak measures the full spread between the earliest and latest errors. A single disturbance, buffer event, or missed sample can widen it dramatically. Use the percentile value to understand the usual behavior when outliers are present.

5) How is TIE computed here?

In period mode, TIE is the running sum of period errors. In timestamp mode, each timestamp is compared to an ideal clock grid starting at the first edge. The tool reports TIE peak to peak to show accumulated wander.

6) Can I export results for reports?

Yes. After a calculation, download a CSV summary for spreadsheets or generate a PDF from the results section. The preview table helps document representative samples alongside the headline metrics.