Sleep Chart



Sleep is vital for learning. To sleep well and to learn well, you need to understand your own circadian rhythm. Sleep Chart in SuperMemo was designed to assist you in that task. It can help you optimize the timing of sleep as well as to optimize the timing of your learning. You can inspect the timeline of learning that is generated automatically. Your sleep data must be logged manually in the Sleep Chart. Collecting your sleep data can be useful in understanding the link between sleep and learning.


You can access Sleep Chart with (1) Tools : Sleep Chart on the Main menu, (2) SuperMemo commander, or (3) by just pressing F12.

SuperMemo: Tools: Sleep & Learning Timeline displaying repetitions blocks of the current collection (in red) and sleep blocks (in blue)


Repetitions timeline


Sleep timeline



Timeline graphs











Circadian and homeostatic sleepiness

Blue line shows how often sleep is initiated at different periods after awakening (% on the vertical axis on the right). This line is a rough reflection of the homeostatic sleep drive. Red line shows how long sleep lasts depending on the hour at which it was initiated (in reference to the hour of morning awakening)(hours on the vertical axis on the left). This line is a rough reflection of the circadian sleep component, i.e. the longest sleep blocks occur during the subjective night. Note that the sleep length graph is slightly phase shifted in reference to the circadian sleep drive due to the fact that long sleep is mostly achieved by initiating sleep too early. In the presented example, on average, the best sleep is obtained when initiated after 18 hours from morning awakening (homeostatic peak combined with a sufficiently long sleep period). This example also shows that the optimum siesta time occurs 7 hours after awakening. For example, for an awakening at 6 am, the siesta should begin at 1 pm, and the night sleep at midnight.

Phase shift





In healthy individuals who are not sleep deprived and who sleep in the correct phase, the best learning results are obtained early in the morning and after a siesta. You can see how fast your alertness, recall and grades drop during the day by inspecting the Alertness (H) graph. In this graph, you can see the time that has passed since the last sleep block, and how your recall changes in waking. The minimum length of sleep blocks that are considered is determined by Min. sleep block (h) box (0.2 hours, or 12 min. is the default minimum sleep block taken into consideration). Shorter sleep blocks are disregarded in plotting this graph.

If you have already collected your sleep data with SleepChart, you can see your wake-recall correlations with the newest SuperMemo. However, only repetitions executed with SuperMemo 2006 or later will count (earlier SuperMemos did not store precise time of repetitions in repetition history).


Alertness (H) graph makes it possible for you to visually inspect how recall decreases during the waking day. It also shows the impact of circadian factors with grades slightly lower immediately after waking and slightly higher after the mid-day dip in the 10-13 hours bracket. The Deviation parameter displayed at the top tells you how well the chosen approximation curve fits the data (in the picture: negatively exponential recall curve). The lesser the deviation, the better the fit. The deviation is computed as a square root of the average of squared differences (as used in the method of least squares).

SuperMemo: Tools : Sleep Chart : Alertness (C) graph makes it possible for you to visually inspect how grades decrease during the waking day.

Alertness (C) graph showing the powerfully biphasic nature of the human circadian cycle. The horizontal axis shows the circadian time, i.e. the time that elapses from phase 0, i.e. the predicted "end of the night" time. The prediction comes from the circadian model employed in SleepChart, and is derived from the sleep log collected in SuperMemo. The pink line is the predicted alertness derived from the same sleep log data using the two-process model of sleep developed for the purpose of sleep optimization in SuperMemo (the model is inspired by similar work by Alexander A. Borbely and Peter Achermann). The alertness is the resultant of the status of the two sleep drive processes: the homeostatic process and the circadian process. The blue dots are recall data taken from an actual learning process in SuperMemo.

Alertness approximation buttons

  • Homeostatic - approximation of the homeostatic alertness (inverse of the homeostatic sleep drive). Depending on the status of the Model button, the approximation is either a theoretical negatively exponential curve that provides the best fit to the alertness data, or is taken from the two-processes model providing best fit to the sleep log data.
  • Circadian - approximation of the circadian alertness (inverse of the circadian sleep drive). Depending on the status of the Model button, the approximation is adjusted for the actual waking time or for the predicted optimum waking time taken from the two-processes sleep model. Depending on the status of the Exp FI button, the graph is also adjusted for the theoretical association between grades and recall (as opposed to only fail vs. success measurement).
  • Alertness - resultant alertness that combines homeostatic and circadian alertness (inverse of the modelled sleep drive). The formula used to combine the two components of alertness has been derived heuristically to provide a good fit to sleep log and recall data.
  • Wake - waking time proportion at a given point in circadian time (this is a straight line in the homeostatic graph as all points in the graph are plotted after the last registered sleep episode). The waking proportion is not to scale as all approximation graphs are stretched between minimum and maximum levels for better graph clarity.

Other alertness graph buttons

  • Model - switch between actual waking time and the modelled predicted optimum waking time taken from the two-processes model. This button also switches to the negatively exponential approximation of the wake-vs-recall curve (as opposed to the curve taken from the two-processes sleep model).
  • Exp FI - use expected forgetting index estimations to differentiate between grades in the learning process (when this button is depressed, only fail and pass grades are taken as recall 0 and 1).
  • Excel - export data to Excel.

Homeostatic alertness parameters

When displaying the homeostatic alertness, you can adjust two parameters (bottom of the graph):

  • minimum length of sleep blocks considered (in hours). All sleep episodes lasting less than the said parameter will be ignored in the graph.
  • homeostatic alertness halflife (in hours). This number tells you when your learning capacity drops by half after waking. You can modify this parameter to look for a better curve fit (Model must be depressed). See Deviation to evaluate the fit. This halflife can differ between individuals. Notably, it is very short in narcoleptics, and very long in natural non-nappers.




Distribution of the length of sleep blocks.

Two-component sleep model








You can abandon SleepChart





You need to copy sleep timeline when reinstalling SuperMemo





Gaps in Timeline


I had been meticulously recording my sleep for about 6 months until I lost track for a couple of weeks and then began recording my sleep once more. How are such gaps in SleepChart treated? Can anything be done afterwards to minimise the damage to the data?



Should I log light sleep


Hello, should log the time from when you get into bed or try to estimate the time at which you actually fall asleep ? I sometimes take up to hours to truly fall asleep even if I am tired. And if I spent an hour on my bed in a kind of light sleep but conscious (or meditating), should I log that in ? Or should I just try to truly sleep when I am in my bed ?


As SleepChart does not provide for differentiating between sleep stages (this would require some advanced measurement technology), you can use conscious mind as the sole indicator. Light sleep with loss of consciousness should mark as blue=sleep, while tossing and turning or meditation without the loss of conscious thinking should mark as white=wake. If you happen to guess you had short moments of sleep (1-2 min.), you could mark these as short vertical blue sleep lines. Whether you are interested in optimizing sleep (e.g. when to go to sleep) or in viewing your learning performance in waking time, SuperMemo shall cope ok with a degree of imprecision in logging sleep in situations like the one described.