Exponential decay

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A quantity undergoing exponential decay. Larger decay constants make the quantity vanish much more rapidly. This plot shows decay for decay constants (λ) of 25, 5, 1, 1/5, and 1/25 for x from 0 to 5.

A quantity is subject to exponential decay if it decreases at a rate proportional to its current value. Symbolically, this process can be expressed by the following differential equation, where N is the quantity and λ (lambda) is a positive rate called the exponential decay constant:

\frac{dN}{dt} = -\lambda N.

The solution to this equation (see derivation below) is: Exponential rate of change

N(t) = N_0 e^{-\lambda t}. \,

Here N(t) is the quantity at time t, and N0 = N(0) is the initial quantity, i.e. the quantity at time t = 0.

Measuring rates of decay[edit]

Mean lifetime[edit]

If the decaying quantity, N(t), is the number of discrete elements in a certain set, it is possible to compute the average length of time that an element remains in the set. This is called the mean lifetime (or simply the lifetime or the exponential time constant), τ, and it can be shown that it relates to the decay rate, λ, in the following way:

\tau = \frac{1}{\lambda}.

The mean lifetime can be looked at as a "scaling time", because we can write the exponential decay equation in terms of the mean lifetime, τ, instead of the decay constant, λ:

N(t) = N_0 e^{-t/\tau}. \,

We can see that τ is the time at which the population of the assembly is reduced to 1/e = 0.367879441 times its initial value.

E.g., if the initial population of the assembly, N(0), is 1000, then at time τ, the population, N(τ), is 368.

A very similar equation will be seen below, which arises when the base of the exponential is chosen to be 2, rather than e. In that case the scaling time is the "half-life".

Half-life[edit]

Main article: Half-life

A more intuitive characteristic of exponential decay for many people is the time required for the decaying quantity to fall to one half of its initial value. This time is called the half-life, and often denoted by the symbol t1/2. The half-life can be written in terms of the decay constant, or the mean lifetime, as:

t_{1/2} = \frac{\ln (2)}{\lambda} = \tau \ln (2).

When this expression is inserted for \tau in the exponential equation above, and ln 2 is absorbed into the base, this equation becomes:

N(t) = N_0 2^{-t/t_{1/2}}. \,

Thus, the amount of material left is 2−1 = 1/2 raised to the (whole or fractional) number of half-lives that have passed. Thus, after 3 half-lives there will be 1/23 = 1/8 of the original material left.

Therefore, the mean lifetime \tau is equal to the half-life divided by the natural log of 2, or:

\tau = \frac{t_{1/2}}{\ln 2} \approx 1.44 \cdot t_{1/2}.

E.g. Polonium-210 has a half-life of 138 days, and a mean lifetime of 200 days.

Solution of the differential equation[edit]

The equation that describes exponential decay is

\frac{dN}{dt} = -\lambda N

or, by rearranging,

\frac{dN}{N} = -\lambda dt.

Integrating, we have

\ln N = -\lambda t + C \,

where C is the constant of integration, and hence

N(t) = e^C e^{-\lambda t} = N_0 e^{-\lambda t} \,

where the final substitution, N0 = eC, is obtained by evaluating the equation at t = 0, as N0 is defined as being the quantity at t = 0.

This is the form of the equation that is most commonly used to describe exponential decay. Any one of decay constant, mean lifetime, or half-life is sufficient to characterise the decay. The notation λ for the decay constant is a remnant of the usual notation for an eigenvalue. In this case, λ is the eigenvalue of the negative of the differential operator with N(t) as the corresponding eigenfunction. The units of the decay constant are s−1.

Derivation of the mean lifetime[edit]

Given an assembly of elements, the number of which decreases ultimately to zero, the mean lifetime, \tau, (also called simply the lifetime) is the expected value of the amount of time before an object is removed from the assembly. Specifically, if the individual lifetime of an element of the assembly is the time elapsed between some reference time and the removal of that element from the assembly, the mean lifetime is the arithmetic mean of the individual lifetimes.

Starting from the population formula

N = N_0 e^{-\lambda t}, \,

we firstly let c be the normalizing factor to convert to a probability density function:

1 = \int_0^\infty c \cdot N_0 e^{-\lambda t}\, dt = c \cdot \frac{N_0}{\lambda}

or, on rearranging,

c = \frac{\lambda}{N_0}.

We see that exponential decay is a scalar multiple of the exponential distribution (i.e. the individual lifetime of each object is exponentially distributed), which has a well-known expected value. We can compute it here using integration by parts.

\tau = \langle t \rangle = \int_0^\infty t \cdot c \cdot N_0 e^{-\lambda t}\, dt = \int_0^\infty \lambda t e^{-\lambda t}\, dt = \frac{1}{\lambda}.

Decay by two or more processes[edit]

A quantity may decay via two or more different processes simultaneously. In general, these processes (often called "decay modes", "decay channels", "decay routes" etc.) have different probabilities of occurring, and thus occur at different rates with different half-lives, in parallel. The total decay rate of the quantity N is given by the sum of the decay routes; thus, in the case of two processes:

-\frac{dN(t)}{dt} = N\lambda _1 + N\lambda _2 = (\lambda _1 + \lambda _2)N.

The solution to this equation is given in the previous section, where the sum of \lambda _1 + \lambda _2\, is treated as a new total decay constant \lambda _c.

N(t) = N_0 e^{-(\lambda _1 + \lambda _2) t} = N_0 e^{-(\lambda _c) t}.

Partial mean life associated with an individual processes is by definition the multiplicative inverse of corresponding partial decay constant: \tau = 1/\lambda. A combined \tau_c can be given in terms of \lambdas:

\frac{1}{\tau_c} = \lambda_c = \lambda_1 + \lambda_2 = \frac{1}{\tau_1} + \frac{1}{\tau_2}
\tau_c = \frac{\tau_1 \tau_2}{\tau_1 + \tau_2}.

Since half-lives differ from mean life \tau by a constant factor, the same equation holds in terms of the two corresponding half-lives:

T_{1/2} = \frac{t_1 t_2}{t_1 + t_2}

where T _{1/2} is the combined or total half-life for the process, t_1 and t_2 are so-named partial half-lives of corresponding processes. Terms "partial half-life" and "partial mean life" denote quantities derived from a decay constant as if the given decay mode were the only decay mode for the quantity. The term "partial half-life" is misleading, because it cannot be measured as a time interval for which a certain quantity is halved.

In terms of separate decay constants, the total half-life T _{1/2} can be shown to be

T_{1/2} = \frac{\ln 2}{\lambda _c} = \frac{\ln 2}{\lambda _1 + \lambda _2}.

For a decay by three simultaneous exponential processes the total half-life can be computed as above:

T_{1/2} = \frac{\ln 2}{\lambda _c} = \frac{\ln 2}{\lambda_1 + \lambda_2 + \lambda_3} = \frac{t_1 t_2 t_3}{(t_1 t_2) + (t_1 t_3) + (t_2 t_3)}.

Applications and examples[edit]

Exponential decay occurs in a wide variety of situations. Most of these fall into the domain of the natural sciences.

Many decay processes that are often treated as exponential, are really only exponential so long as the sample is large and the law of large numbers holds. For small samples, a more general analysis is necessary, accounting for a Poisson process.

Natural sciences[edit]

  • Electrostatics: The electric charge (or, equivalently, the potential) stored on a capacitor (capacitance C) decays exponentially, if the capacitor experiences a constant external load (resistance R). The exponential time-constant τ for the process is R C, and the half-life is therefore R C ln2. (Furthermore, the particular case of a capacitor discharging through several parallel resistors makes an interesting example of multiple decay processes, with each resistor representing a separate process. In fact, the expression for the equivalent resistance of two resistors in parallel mirrors the equation for the half-life with two decay processes.)
  • Fluid Dynamics: A fluid emptying from a tube with an opening at the bottom will empty at a rate which depends on the pressure at the opening (which in turn depends on the height of the fluid remaining). Thus the height of the column of fluid remaining will follow an exponential decay.
  • Heat transfer: If an object at one temperature is exposed to a medium of another temperature, the temperature difference between the object and the medium follows exponential decay (in the limit of slow processes; equivalent to "good" heat conduction inside the object, so that its temperature remains relatively uniform through its volume). See also Newton's law of cooling.
  • Luminescence: After excitation, the emission intensity - which is proportional to the number of excited atoms or molecules - of a luminescent material decays exponentially. Depending on the number of mechanisms involved, the decay can be mono- or multi-exponential.
  • Radioactivity: In a sample of a radionuclide that undergoes radioactive decay to a different state, the number of atoms in the original state follows exponential decay as long as the remaining number of atoms is large. The decay product is termed a radiogenic nuclide.

Social sciences[edit]

  • Finance: a retirement fund will decay exponentially being subject to discrete payout amounts, usually monthly, and an input subject to a continuous interest rate. A differential equation dA/dt = input - output can be written and solved to find the time to reach any amount A, remaining in the fund.
  • In simple glottochronology, the (debatable) assumption of a constant decay rate in languages allows to estimate the age of single languages. (To compute the time of split between TWO languages requires additional assumptions, independent of exponential decay).

Computer science[edit]

  • The core routing protocol on the Internet, BGP, has to maintain a routing table in order to remember the paths a packet can be deviated to. When one of these paths repeatedly changes its state from available to not available (and vice-versa), the BGP router controlling that path has to repeatedly add and remove the path record from its routing table (flaps the path), thus spending local resources such as CPU and RAM and, even more, broadcasting useless information to peer routers. To prevent this undesired behavior, an algorithm named route flapping damping assigns each route a weight that gets bigger each time the route changes its state and decays exponentially with time. When the weight reaches a certain limit, no more flapping is done, thus suppressing the route.

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