Will output optimal graduation mark based on current students, phi, and tau values. Instructions on how to run are found in Introduction to Graduation.
If you want to track your daily tau gains and contribute to daily tau rates graphs, request for access on this sheet. F(t) and Tau graphs available.
Leaderboards for highest τ and publication multi of each theory, highest positive and negative ρ of each lemma, highest overall and minigame stars, and a monthly updated cross platform F(t) rankings.
Get confused with all the variables in BaP, FP, and TC? Get tired in calculating the ratio of to other variables? Tired of checkig the sim for purchasig variable? Here introduce a convenient tool to instantly check which variables to buy next! All u need is the levels of the variables at the current stage, and it will calculate automatically for u! Made by Hackzzzzzz.
Will output optimal graduation mark based on current students, phi, and tau values. Instructions on how to run are found in Introduction to Graduation.
If you want to track your daily tau gains and contribute to daily tau rates graphs, request for access on this sheet. F(t) and Tau graphs available.
Leaderboards for highest τ and publication multi of each theory, highest positive and negative ρ of each lemma, highest overall and minigame stars, and a monthly updated cross platform F(t) rankings.
Get confused with all the variables in BaP, FP, and TC? Get tired in calculating the ratio of to other variables? Tired of checkig the sim for purchasig variable? Here introduce a convenient tool to instantly check which variables to buy next! All u need is the levels of the variables at the current stage, and it will calculate automatically for u! Made by Hackzzzzzz.
Publications are equivalent to prestiges for so don’t be afraid to
use them. However, the best publication multipliers vary from theory to theory and will
change over time. If you are close to a multiplier you want, turn off autobuyer
and let increase without buying upgrades for a faster short-term increase
before the publication (turn on after you publish). This is known and referenced as “coasting”.
Total , found in the equation or at the top of the screen, is a multiplicative
combination of all from each theory.
Don’t be afraid to skip getting all milestones to work on the next or a
better theory.
In mathematics, a recurrence relation is an equation that relies on an
initial term and a previous term to change.
We start with the current tick’s term, , and a constant add-on to
obtain the value of the next tick, . This gives us an equation
equivalent to , with a changing value and a constant
that is the initial value of 1. Later when we add the term,
this is now saying that we are now adding each tick the value of from
the previous tick ago with a constant put to the power of . This
is the same with the next term , with the value of two ticks
ago and a multiplier put to the power . When we multiply the
term by the term changing the constant addition to
being based on the value of from the previous tick with the value of
. The final milestone upgrade raises the exponent of from
to to to .
This theory also has its adjusted tickspeed calculated by . This
lengthens the normal tick length of to that value which speeds
up the theory.
The publication multiplier has no optimal fit, as it fluctuates a lot,
but here is known: 4-6 to start; 3-4 between and ; the
publication multiplier oscillates between 2.5 and 5 past . Once you
get your first milestone, you can turn off and until active strat.
The active strat follows but only works when you have all milestones
past . T1 is the only theory where the recent value of
influences the rate of change of therefore buying a variable as
soon as you can afford it will slow your progress. Lategame, buying
upgrades immediately will slow you more than the benefit of the upgrade
because and dominate. If the next level costs
and you have , buying that level will reduce to . This reduces your by roughly a factor of .
There are terms that influence the rate of change of , and all are affected by the previous state of . The active strategy around this is known as T1Ratio. The values in the chart found here are to be
only used when you are past and max milestones. They represent how to purchase each variable based on the state of the theory at the time of purchase.
Note: If you are not doing the active strat, then simply turn off and after milestone 1 () and autobuy rest until ee6k.
The video below is only good for early between and .
This second theory is focusing on derivatives. Derivatives in
mathematics are the rate of change of the function they are the
derivative of. For the case of and , is
the derivative of . This follows the power rule for derivatives:
In simpler terms, it works similar to how
upgrades work for equation with continuous addition
of the previous to the next term, but with
continuous addition of to the term above .
These two values of and are multiplied to produce the derivative
of , shown by Newton’s derivative notation . This would give the
equation of to be . The other milestones besides more
and derivatives increase the exponent of and respectively. The
reason why and derivatives are more powerful long-term than the
exponents is that they take time to build up and eventually overtake and
keep increasing and while the exponents have a never-changing
boost.
The optimal multiplier is pretty high and is not known before . The theory sim will recommend publication multipliers below these values, but the sim’s T2MS does not currently have coasting.
The multipliers for active play (which do use coasting) we know at the moment are:
- is to
- is -
For both strategies the milestones are listed in the order X>Y, where X and Y are the milestones as numerically ordered top to bottom in-game, are to be maxed in order from left to right.
For the idle strategy, you want to prioritize buying milestone levels of 1>2. If you have more than 4 milestones, you will prioritize
milestone 1>2>3>4. You will want to publish at
about 10-100 multiplier before and about a multiplier after , but larger multipliers are fine.
If possible, swap to milestones 3>4>1>2 at the end before publishing for an additional boost.
The goal of the active strategy is to grow and as
much as possible while being able to take advantage of the exponent
milestones too, yielding a large boost from that growth. The active for T2 is on a 50-second cycle between two milestone sets: 10 seconds for
exponent priority (Milestones 3 and 4) and 40 seconds for derivative priority (Milestones 1 and 2) . You will start a publication with exponent priority as the cost of the variables gained from milestones 1 and 2 are
too large for you to get right away. When you can afford them, you will
start the cycle. The full cycle is listed below:
Past , the active strat will become exponentially less
effective. At , you would start to idle T2 overnight only.
Until you have over from theory 2, this is the best theory
to run idle overnight.
When you get to Theory 3 at ee7k, move on to pushing Theory 3 when active and running T2 overnight. The above is simply an option if you rather not work on T3 now.
The basis of this theory and understanding how it works is based on
matrix multiplication. The following color-coding helps displays
how matrix multiplication works:
This gives the basis for why certain upgrades are more powerful than
others. The exponents on , , and
all directly affect production which is used for . An extra
dimension roughly gives more production as it adds an extra term
to the production.
The optimal publication multiplier is about 2-3 without cruising and 3-4
with cruising. If you decide to play actively, there is a form of
exponent swapping strat to be aware of. This is a difficult
strategy because it requires you to notice when a certain threshold
happens. It happens when the following occurs:
\[c_{11}*b_{1}^{1.05\text{ or }1.1}<c_{12}*b_{2}^{1.05\text{ or }1.1}\]
When this happens swap your exponents from to and you will get a
little upgrade boost. It also allows for a slight push of for
upgrades to and , but this is a lot less impactful and less
noticeable. This strategy also works with and but is usually
not as common.
If you decide to buy manually, the focus areas are buying , , and when their cost is
e1 lower than , , and respectively. These all directly boost the production
of which is used for . After this, if you are doing the active exponent
swapping strategy described in the previous paragraph, your next focus will be on ,
, and as these boost production which increases the likelihood
for the exponent swap to occur. This leaves the , , and
upgrades at the lowest priority. If you are not using the exponent
swapping strategy from the previous paragraph, then all the remaining
upgrades should be bought at equivalent priority.
At the end of any publication, around a 2-3 multiplier, you should turn
off and as they cost . You will cruise until you get to a
3-4 multiplier. Publish and turn back on costing variables and
repeat.
Theory 4 is based on Polynomials, which contain terms of the form etc. In this case, instead of ‘x’ it’s ‘q’. The strategies for this theory are quite simple compared to the previous theory, especially late game strategies.
The first line states that the rate of change of is the sum of a bunch of polynomial terms. We have a bunch of ‘c’ variables multiplied by ‘q’. We can increase by buying and upgrades. Note that this is with all milestones. You’ll not have all of these at the beginning.
The second line is more unique. It says that is proportional to the inverse of itself! This means that the more we have, the slower grows, as decreases. This means that and are not as strong as they first appear. However, we still want to buy them in general unless stated otherwise as slow growth is better than no growth.
For the more mathematically observant reader, we may integrate the equation and conclude that is proportional to the square root of time. This means that even though grows slower with increasing , there is theoretically no finite limit on the maximum value of .
Approximate variable strengths on with all milestones are as follows:
Class: breakdown;
INVIS
Brief Description
[type=“th”;]
~7% increase on the term (instantaneous).
[type=“th”;]
Doubles the term (instantaneous). Note that this doesn’t mean double
[type=“th”;]
Doubles the term (instantaneous).
[type=“th”;]
Doubles the term (instantaneous).
[type=“th”;]
Doubles the term (instantaneous).
[type=“th”;]
Doubles the term (instantaneous).
[type=“th”;]
~7% increase on . Note that because of the square root relationship between time and mentioned earlier, this translates to ~3.5% increase in long term . No instantaneous effect on .
[type=“th”;]
Doubles the instantaneous value of . Note that because of the square root relationship between time and mentioned earlier, this translates to ~41% increase in long term . No instantaneous effect on .
T4 is quite idle friendly compared to T3 and T1. Here are some simple idle strategies for T4:
Start to e25:
Autobuy , . DON’T buy , , ! The term is bad early on. Publish at ~2.5-3 if possible.
e25 to e175:
Get the ‘Add the term’ milestones. Prioritize these ones first until maximum. Now autobuy , , ONLY. Best publication multiplier is ~6-7.
When and are unlocked, add and to the autobuy variables. DON’T autobuy , , ! Prioritize the milestones over the exponents. Try to publish between 12-20.
e175 to endgame:
Simply autobuy , , ONLY. Buy 1 level of to start the theory. Publish at ~4-5.
There’s no strategic difference between semi-idle and idle for this theory. The main difference is with semi-idle, we would publish more often since we check the game more often. We wouldn’t overshoot the optimal multiplier as much.
T4 active is more involved. However it is not as demanding as T3 or T1 active.
Start to e75:
Autobuy . DON’T buy , , ! The term is bad early on. Buy until its cost exceeds about 15% of cost. Publish at about 2.5-3 if possible. When we reach , we get the exponent milestone (note the difference between this strategy and the idle strategy). With the exponent milestone, the term remains the strongest term IF we can babysit and publish often (at about 2.5-3). The strategy remains the same otherwise. Note that since we’re only buying and (NO , , , , , !), all the ‘q’ related milestones are useless for now.
e75 to e175 OR 14k f(t):
Now here is where we can apply some more advanced strategies. Consider that the term is strong early on, but falls off as the value of increases. Then we can conclude that we can start with the same strategy as before. But once we reach our previous publication point, we can switch to the following strategy:
Do the same strategy as before until we reach our previous publication point.
Take point(s) out of the exponent milestones and unlock all the terms (the first milestone). We should now have access to .
Autobuy , , , .
If you want to optimize a bit more, you can buy until its cost exceeds about 15% of . Otherwise it’s ok to also autobuy .
DO NOT autobuy , , .
Publish at ~10-20. Once published, remember to take out the milestone point and put it back into the exponent to repeat step 1.
If done right, this strategy is significantly faster than the idle strategies above. The logic with this strategy is that the , , terms scale well with ‘q’. However we need enough to buy a lot of q. So in the beginning we buy only as usual to accumulate enough so that we can buy to stack q. Once we have enough q, the , , terms will outscale. Note that after e14k , we will unlock certain upgrades that make better again.
e175 OR 14k f(t) to ~e300 T4
We will do the exact same strategy as in the #start to section above. This is because become really strong again and the terms take too long to outscale. Note that we still don’t buy .
~e300 to endgame
At this point the term starts to become dominant. Therefore we will prioritize buying , , . We will NOT buy anything else except 1 level of to start the theory. If you wish, you can buy at about 15% ratio to cost. It is also ok to autobuy . The term will remain dominant until endgame.
Before you reach 9k, these are the recommended values for each theory.
You may not hit the values and have a different distribution, but work on getting these theories up to these values later. This list is in order of priority.