Update README.md

README.md

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-license: mit
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+---
+license: mit
+---
+# PhyTS Dataset
+## Abstract
+ We introduce PhyTS, a benchmark suite of precision scientific time series datasets for machine learning, spanning experiments in gravitational-wave detection, dark matter searches, neutrino mass determination, and stellar variability detection. Despite their diverse scientific goals, these domains share a common challenge: recovering weak, structured signals and estimating underlying physical parameters from noise-dominated measurements.
+Unlike standard sequence modeling benchmarks such as audio and speech, these data exhibit non-Gaussian and nonstationary noise, long-range temporal correlations, detector-specific systematics, irregular sampling, and signals that are sparse, weak, or only partially modeled. As a result, they provide a challenging testbed for evaluating whether modern AI methods can support downstream scientific inference.
+We provide standardized tasks, data splits, and evaluation protocols for denoising, signal recovery, and parameter inference across physics domains, along with baseline results. By unifying diverse weak-signal inference problems under a common framework, this benchmark aims to enable reproducible evaluation and accelerate the development of more robust, interpretable, and physically grounded methods for scientific time series analysis.
+> [!NOTE]
+> 📌 Github repo: [kyoon-mit/TimeSeriesPhysics](https://github.com/kyoon-mit/TimeSeriesPhysics)
+
+## LIGO
+
+### LIGO Dataset Field Description
+
+## TESS
+
+### TESS Dataset Field Description
+
+## TIDMAD
+The TIDMAD dataset is broken into training and validation data which are identically constructed differing only by the time at which the detector data was taken. 
+This temporal difference results in variable detector noise conditions. 
+There are 20 hdf5 files (~ 4 GB/file) in both training and validation datasets. 
+The total dataset size is 163 GB.
+Each file contains ~ 200 examples and the associated meta data. 
+Each example is a set of ch1 time series, ch2 time series, and injected frequency. 
+This data in each hdf5 file includes the following
+### TIDMAD Dataset Field Description
+
+| Parameter | Type / Size | Description |
+|-----------|-------------|-------------|
+| `chunk_length` | dtype=int | Number of samples per example |
+| `n_chunks` | dtype=int | Number of examples per file |
+| `sample_rate_hz` | dtype=int | Data taking sample rate in Hz |
+| `signal_freq_choices` | size=(618,1), dtype=int | Array of signal frequencies injected across the full dataset, all files |
+| `signal_frequency` | size=(200,1), dtype=int | Injected frequency for the example in Hz (`signal_frequency[i]` is the injected signal frequency for example `i`) |
+| `time_series_ch1` | size=(200,10M), dtype=int | Noisy time series for the example in DAQ units (`time_series_ch1[i]` is the ch1 time series for example `i`) |
+| `time_series_ch2` | size=(200,10M), dtype=int | Signal time series for the example in DAQ units (`time_series_ch2[i]` is the ch2 time series for example `i`) |
+
+
+## Project 8
+
+### Project 8 Dataset Field Description