Drawing conclusions by looking at integral

In summary, the integral ##I## can be expressed as an integral over the entire real line, and a counterexample can be constructed using a symmetric distribution ##f_x## that has two delta-function peaks at ##\pm b##. This leads to a contradiction with the proposed statement that ##I## must be positive if the area under the graph on the negative ##p##-axis is smaller than that on the positive ##p##-axis.
  • #1
WWCY
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Homework Statement



I have the following expression

$$I = \int_{-\infty}^{0} f_p(p) \ \big[ pf_x(a - \frac{p}{m}t) \big] dp + \int_{0}^{\infty} f_p(p) \ \big[ pf_x(a - \frac{p}{m}t) \big] dp$$

where ##f_p## and ##f_x## are normalised distributions. In particular, ##f_x## is symmetric about ##x=a##. This also means that ##pf_x(a - \frac{p}{m}t) ## is anti-symmetric about ##p = 0##.

Is there any way through which I can prove (or disprove) that ##I## is positive if
$$\int_{-\infty}^{0} f_p(p) dp < \int_{0}^{\infty} f_p(p) dp $$
ie the area under the graph on the -ve ##p##-axis is smaller than that on the +ve ##p##-axis?

Some guidance regarding how to start is greatly appreciated. Thanks in advance!

Homework Equations

The Attempt at a Solution

 
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  • #2
I would try to express the (negative) left side wrt the (positive) side. I.E. something like - (int_0^+inf, the integrand will change but you have properties of f and f_x to help you out. PLEASE, let me know if/how that helps.

(Dr.) Dave
 
  • #3
Can't you come up with a counterexample where ##f_p(p)## and ##g_p(p) = pf_x(a-\frac pm t)## don't overlap so that ##I=0##?
 
  • #4
Thank you both for replying!

To Dr Dave:
David Dyer said:
I would try to express the (negative) left side wrt the (positive) side. I.E. something like - (int_0^+inf, the integrand will change but you have properties of f and f_x to help you out. PLEASE, let me know if/how that helps.
hmm, does this not assume that ##f_p## is symmetric about 0 as well? I'm not sure I'm allowed to make such an assumption in my problem if that is the case.

To vela:
vela said:
Can't you come up with a counterexample where ##f_p(p)## and ##g_p(p) = pf_x(a-\frac pm t)## don't overlap so that ##I=0##?
So if I have ##g_p (p)## that asymptotes at about ##p = \pm 5## ,and I have a ##f_p## that has gaussian peaks at ##p = -1## (area of ~ 0.4) and ##p = 20## (area of ~0.6), I can even have a negative value for ##I## despite ##\int_{-\infty}^{0} f_p(p) dp < \int_{0}^{\infty} f_p(p) dp##

Is this right?
 
  • #5
WWCY said:

Homework Statement



I have the following expression

$$I = \int_{-\infty}^{0} f_p(p) \ \big[ pf_x(a - \frac{p}{m}t) \big] dp + \int_{0}^{\infty} f_p(p) \ \big[ pf_x(a - \frac{p}{m}t) \big] dp$$

where ##f_p## and ##f_x## are normalised distributions. In particular, ##f_x## is symmetric about ##x=a##. This also means that ##pf_x(a - \frac{p}{m}t) ## is anti-symmetric about ##p = 0##.

Is there any way through which I can prove (or disprove) that ##I## is positive if
$$\int_{-\infty}^{0} f_p(p) dp < \int_{0}^{\infty} f_p(p) dp $$
ie the area under the graph on the -ve ##p##-axis is smaller than that on the +ve ##p##-axis?

Some guidance regarding how to start is greatly appreciated. Thanks in advance!

Homework Equations

The Attempt at a Solution


Let ##I = I_1 +I_2,## where ##I_1## is the first integral and ##I_2## is the second one. Putting ##p = -p'## in ##I_2## we have
$$I_2 = \int_{\infty}^0 f_p(-p') (-p') f_x\left(a + \frac{p'}{m}t \right) (-dp')\\ = -\int_0^{\infty} f_p(-p') p' f_x\left(a +\frac{p'}{m}t \right) \, dp'.$$
Now change the integration variable back to ##p## and use symmetry of ##f_x##, to get
$$I = \int_0^{\infty} p [f_p(p)-f_p(-p)] f_x\left(a - \frac{p}{m} t \right) \, dp.$$
 
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  • #6
Ray Vickson said:
Let ##I = I_1 +I_2,## where ##I_1## is the first integral and ##I_2## is the second one. Putting ##p = -p'## in ##I_2## we have
$$I_2 = \int_{\infty}^0 f_p(-p') (-p') f_x\left(a + \frac{p'}{m}t \right) (-dp')\\ = -\int_0^{\infty} f_p(-p') p' f_x\left(a +\frac{p'}{m}t \right) \, dp'.$$
Now change the integration variable back to ##p## and use symmetry of ##f_x##, to get
$$I = \int_0^{\infty} p [f_p(p)-f_p(-p)] f_x\left(a - \frac{p}{m} t \right) \, dp.$$

Thank you so much for helping out!

Edit: Does this apply to ##I_1## instead of ##I_2##? I'm am not really able to see why the integration limits for ##I_2## carry the same sign despite the change in variables.
 
  • #7
WWCY said:

Homework Statement



I have the following expression

$$I = \int_{-\infty}^{0} f_p(p) \ \big[ pf_x(a - \frac{p}{m}t) \big] dp + \int_{0}^{\infty} f_p(p) \ \big[ pf_x(a - \frac{p}{m}t) \big] dp$$

where ##f_p## and ##f_x## are normalised distributions. In particular, ##f_x## is symmetric about ##x=a##. This also means that ##pf_x(a - \frac{p}{m}t) ## is anti-symmetric about ##p = 0##.

Is there any way through which I can prove (or disprove) that ##I## is positive if
$$\int_{-\infty}^{0} f_p(p) dp < \int_{0}^{\infty} f_p(p) dp $$
ie the area under the graph on the -ve ##p##-axis is smaller than that on the +ve ##p##-axis?

Some guidance regarding how to start is greatly appreciated. Thanks in advance!

Homework Equations

The Attempt at a Solution

I think the result is incorrect.

First note that you can write your integral ##I## as
$$I = \int_{-\infty}^{\infty} p f_p(p) f_x\left(a- \frac{pt}{m} \right) \, dp$$
Now consider a special case of
$$f_x(w) = \frac{1}{2} \delta(w+b) + \frac{1}{2} \delta(w-b),$$
where ##\delta(u) ## is the Dirac delta-function and ##b > 0##. The delta-function is even, so ##f_x## is also even in ##w##.

Now we get
$$I = \frac{m^2}{2 t^2} \left[(a+b)f_p\left(\frac{m(a+b)}{t} \right) +(a-b) f_p\left(\frac{m(a-b)}{t} \right) \right] \hspace{5ex}(1)$$
By playing with the function ##f_p## and the value of ##b## it will be possible to have ##I < 0## in some cases, but ##I > 0## in other cases.

Of course, you could object that the Dirac delta is not a true, "legitimate" function, but it IS a limit of a sequence of true functions, and so there are true functions that essentially mimic eq. (1), and so give counterexamples to what you hoped.
 
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  • #8
Ray Vickson said:
I think the result is incorrect.

First note that you can write your integral ##I## as
$$I = \int_{-\infty}^{\infty} p f_p(p) f_x\left(a- \frac{pt}{m} \right) \, dp$$
Now consider a special case of
$$f_x(w) = \frac{1}{2} \delta(w+b) + \frac{1}{2} \delta(w-b),$$
where ##\delta(u) ## is the Dirac delta-function and ##b > 0##. The delta-function is even, so ##f_x## is also even in ##w##.

Now we get
$$I = \frac{m^2}{2 t^2} \left[(a+b)f_p\left(\frac{m(a+b)}{t} \right) +(a-b) f_p\left(\frac{m(a-b)}{t} \right) \right] \hspace{5ex}(1)$$
By playing with the function ##f_p## and the value of ##b## it will be possible to have ##I < 0## in some cases, but ##I > 0## in other cases.

Of course, you could object that the Dirac delta is not a true, "legitimate" function, but it IS a limit of a sequence of true functions, and so there are true functions that essentially mimic eq. (1), and so give counterexamples to what you hoped.

I believe I see it clearly now, many thanks for your assistance!
 

What is an integral and how is it used in drawing conclusions?

An integral is a mathematical concept that represents the area under a curve on a graph. It is commonly used in calculus to find the total change or accumulation of a quantity over a given interval. In drawing conclusions, integrals can be used to analyze and interpret data by calculating the overall change or trend in a set of values.

What is the process for using integrals to draw conclusions?

The process for using integrals to draw conclusions involves first identifying the data or function that needs to be analyzed. Then, the integral is calculated to find the area under the curve or the total change in the data over a specific interval. This value can then be compared to other data points or used to make predictions and draw conclusions about the overall trend or pattern.

What are some real-world applications of using integrals to draw conclusions?

Integrals can be used in a variety of fields to draw conclusions and make predictions. For example, in economics, integrals can be used to analyze supply and demand curves and determine the total revenue or cost for a specific product. In physics, integrals can be used to calculate the work done by a force and determine the displacement of an object. In biology, integrals can be used to analyze growth rates and population dynamics.

Are there any limitations to using integrals to draw conclusions?

While integrals can be a powerful tool for drawing conclusions, there are some limitations to keep in mind. One limitation is that integrals can only be used for continuous data, so they may not be applicable for discrete or non-linear data sets. Additionally, integrals may not be accurate if the data is highly variable or contains outliers.

What are some alternative methods for drawing conclusions besides using integrals?

There are many other methods for drawing conclusions besides using integrals. These include statistical analysis, regression analysis, and data visualization techniques such as scatter plots and histograms. The most appropriate method will depend on the type of data and the specific research question being addressed.

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