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Equation 4 · Seventy-Five Thousand Generations of E. coli, and Counting

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wopen(t)=1+a tβw_{\text{open}}(t) = 1 + a\,t^{\beta}

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Inputs and operations1 + at^β
Result or conditionw_open(t)
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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.

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wopenw_{\text{open}}

Symbol w_open

wow_open is part of the quantity the equation computes from the expression on the right.

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tt

Symbol t

t is an argument of the function-like quantity on the left; its role is set by that function’s stated inputs.

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aa

Symbol a

a is one of the signed contributions combined to compute the quantity on the left.

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tβt^{\beta}

Symbol t^β

t^β is one of the signed contributions combined to compute the quantity on the left.

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=

=

The expressions on both sides represent the same quantity under the stated assumptions.

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addition

addition

Add the term after the plus sign to the term or group before it.

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subscript

subscript

The lower label selects a particular version, component, or indexed member of the quantity. For example, x₀ and xₜ can be values at different positions.

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superscript

superscript

A raised number can be a power. When it is a label or bound, it selects a case or the upper limit of a sum; the formula’s structure distinguishes these uses.

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How to interpret it

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What the article says around this equation

which approaches a fixed value of 1 + a/b as t grows without bound, and wopen(t)=1+a tβw_{\text{open}}(t) = 1 + a\,t^{\beta}. for an exponent β\beta between 0 and 1, which keeps rising — more and more slowly, but without any asymptote — for every value of t . Wiser and colleagues derived the second form theoretically from a model combining clonal interference with diminishing-returns epistasis among beneficial mutations, and reported that across 50,000 generations of real data, “mean fitness appears to increase without bound, consistent with a power law” [ 2 ] . The decelerating rate that Lenski’s 1991 paper had already observed over the first 2,000 generations turns out to be compatible with no ceiling at all: a…
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which approaches a fixed value of 1 + a/b as t grows without bound, and wopen(t)=1+a tβw_{\text{open}}(t) = 1 + a\,t^{\beta}. for an exponent β\beta between 0 and 1, which keeps rising — more and more slowly, but without any asymptote — for every value of t . Wiser and colleagues derived the second form theoretically from a model combining clonal interference with diminishing-returns epistasis among beneficial mutations, and reported that across 50,000 generations of real data, “mean fitness appears to increase without bound, consistent with a power law” [ 2 ] . The decelerating rate that Lenski’s 1991 paper had already observed over the first 2,000 generations turns out to be compatible with no ceiling at all: a population’s fitness gains can keep shrinking, generation after generation, without the sum of those gains ever stopping. That is a specific, falsifiable claim about the shape of adaptation, not a synonym for “still improving.”

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