> For the complete documentation index, see [llms.txt](https://docs.rootcause.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rootcause.ai/more-details/digital-twin/temporal-simulations.md).

# Temporal Simulations

A **temporal** Digital Twin — one built on time-series data — supports its own family of simulations, parallel to the [static simulation types](/more-details/digital-twin/simulation-types.md) but aware of time. Where a static simulation answers a question about a single moment, a temporal simulation answers it across a horizon: not "what is the outcome?" but "how does the outcome evolve, step by step?"

The system sets a twin's type to Temporal automatically when it detects a time column during [twin creation](/user-guide/creating-digital-twin.md). On a temporal twin, the **New Simulation** picker shows the temporal family in place of the static one.

## The temporal family

| Type                                                                    | Question it answers                                                        | Static counterpart       |
| ----------------------------------------------------------------------- | -------------------------------------------------------------------------- | ------------------------ |
| [Forecast](/more-details/digital-twin/temporal-simulations/forecast.md) | How will these variables evolve over the next *n* steps?                   | Prediction               |
| **Temporal Intervention**                                               | How does a time-bounded change affect outcomes over time?                  | Intervention             |
| **Temporal Optimization**                                               | What actions over time best meet a goal, given constraints?                | Optimization             |
| **Temporal Best Action**                                                | What is the minimum change over time needed to reach a target?             | Best Action              |
| **Temporal Explanation**                                                | What time-dependent relationships drive an outcome?                        | Explanation              |
| **Time-Series Root Cause Analysis**                                     | How did a variable drift from its expected trajectory, and what caused it? | Root Cause Analysis      |
| **Time-Series Anomaly Scan & Diagnosis**                                | Which timesteps are anomalous, and why?                                    | Anomaly Scan & Diagnosis |
| **Causal Health Monitor**                                               | What emerging issues should I be alerted to before they escalate?          | *(temporal only)*        |

The types shipping today are [**Forecast**](/more-details/digital-twin/temporal-simulations/forecast.md) (which has a dedicated page), **Temporal Intervention**, and the **Causal Health Monitor** — both covered in [Step 6: Run Simulations](/user-guide/simulations.md). The remaining counterparts in the table are rolling out and appear in the **New Simulation** picker as they ship. Panel time-series twins get the available types as per-environment **Panel** variants.