The original cover identifies the examination as 9 September 2015.[ref]
The image of a function is
The function is surjective, or onto, exactly when every equals for at least one , equivalently . It is injective, or one-to-one, exactly when
Thus surjectivity concerns whether the entire codomain is reached; injectivity concerns whether distinct inputs have distinct outputs.
Since , the image of a function is contained in . Both endpoints occur, at and . By continuity and the intermediate value theorem applied on , every intermediate value occurs too. Hence
It is not surjective onto because, for example, is not attained. It is not injective because although .
If , then and , so . Thus the function is strictly increasing on its domain and is injective. Its values are nonnegative, so it is not surjective onto :
If means its image of a function is ; if it includes zero its image of a function is . Indeed, for any , set and ; then . This convention does not change the classification.
With the convention , the even inputs map to for , while the odd inputs map to for . These two images of a function are disjoint and together equal . Within either class there are no repeated outputs. More explicitly the inverse function is
Consequently is both injective and surjective, hence a bijection. If instead , the input zero is absent: remains injective but its image of a function is , so it is not onto. The printed paper does not specify this convention; the zero-based convention gives the apparent intended bijection.
Take every complement of a set relative to . By set difference, De Morgan's laws, and distribution of set intersection over set union,
Here the middle term is the empty set, since a set and its complement of a set are disjoint.
Use set difference, associativity of set intersection, and De Morgan's laws:
The commutativity and associativity of set intersection give
Equivalently, part (ii) reduces both sides to removal of the same set union .
For every set , the definition of a power set gives
Equality by identical membership therefore proves
The essential observation is that being a subset of a set intersection means being a subset of both factors.
First suppose the sets are finite, with cardinalities and . The power set and Cartesian product counting rules give
Since , the desired inequality follows.
The power-set product cardinality inequality also has an injection proof that does not assume finiteness. Choose distinct and distinct . For and , define the subset of
These three encoding regions are disjoint. The row with second coordinate recovers ; the column with first coordinate and second coordinate different from recovers ; the extra position records whether . Thus is injective, proving for arbitrary sets
Encoding by alone would fail: all pairs with either factor empty would have the same output.
Let be the number of objects in box . The arrangements correspond exactly to nonnegative integer solutions of . By stars and bars, place stars and separating bars in a row. The number of stars between consecutive bars records the occupancy of each distinguishable box, with adjacent bars allowing an empty box. Choosing the bar positions gives
Put one object into each box first. The remaining objects can be distributed without restrictions, so stars and bars gives
Equivalently, the substitution gives a bijection between positive integer solutions of and nonnegative integer solutions of .
Use mathematical induction. For , the left side is . If the identity holds at , then
The base case and induction step establish the geometric series identity
For the base case , , since multiplying by reduces this to . Suppose the claimed inequality holds for some . The identity
then gives
Thus mathematical induction proves
The initial values of the two sequences agree: and . For , use the first-order recurrence relation at and :
Therefore satisfies exactly the same derangement recurrence as . By strong induction, equality of the preceding two terms implies equality of the next term. Consequently
The first-order recurrence relation therefore also counts derangements.
For a binary relation , reflexivity means for every ; a symmetric relation satisfies for every ; an antisymmetric relation satisfies for every ; transitivity means for every ; an irreflexive relation satisfies for every . In particular, failure of reflexivity means at least one missing diagonal pair, whereas irreflexivity requires every diagonal pair to be missing.
There are possible ordered pairs and hence binary relations. A reflexive relation must contain the diagonal pairs, while its remaining pairs are unrestricted. Subtracting the reflexive relations gives
binary relations that are not reflexive.
A symmetric relation has independent choices on the diagonal. For each of the unordered pairs of distinct elements, either both ordered pairs are included or neither is. Thus there are symmetric relations, so the requested number is
For each unordered pair with , antisymmetry allows three choices: neither direction, only , or only . This contributes . The diagonal is unrestricted by antisymmetry, but being not irreflexive requires a nonempty subset of the diagonal pairs. There are such choices. Hence
This allows some diagonal pairs to be absent; “not irreflexive” does not require a reflexive relation.
Because is positive, the definition of big O notation becomes
Here and are fixed independently of .
We prove the stronger bound for every by strong induction. The initial case is . For , put . Then , so the induction hypothesis and the defining recurrence relation give
Thus
The recurrence relation must be read as applying for ; applying it at would invoke outside the printed domain. No value of is needed.
By modular arithmetic, and for some integers . Adding gives
Since is an integer, this proves
Using with integers ,
The quantity in parentheses is an integer, so the divisibility criterion for modular arithmetic gives
By Euclidean division, write and , with integers and . The hypothesis is . Apply the addition rule from part (b)(i) with to obtain
Therefore . But , and the only multiple of in that interval is zero. Hence
so the two remainders agree.
The decimal expansion is . Since , repeated use of the multiplication rule in part (b)(ii) gives for every . Repeated use of the addition rule in part (b)(i) now gives
If , the left side is congruent to zero, whence
This is the decimal digit-sum divisibility test for three, derived directly from modular arithmetic.
Set . The definition of the floor function gives . Adding the integer yields
Since is an integer, it is exactly the floor of . Thus
Put . Because , is a nonnegative integer, and
The function is strictly increasing for , so . Both powers are integers. Taking the floor function therefore gives
Taking nonnegative th roots now gives . Consequently
The argument also covers , when both outer floors are zero.
By the fundamental theorem of calculus,
For the composite trapezoidal rule, the mesh width is and the nodes are . The endpoint weights are halves and the interior weights are ones, so
This formula is an approximation to the definite integral, not an exact equality with it for finite .
Let . The expression in part (ii) gives
Because is continuous on , the composite trapezoidal rule converges to its definite integral, which is by part (i). In fact its standard composite trapezoidal error bound is , since . Therefore
Taking the partial derivatives of the parabolic coordinates transformation, holding the other coordinate fixed each time, gives
Thus its Jacobian matrix is .
The determinant of the Jacobian matrix is . Wherever , the inverse function theorem permits a local inverse of the parabolic coordinates transformation, and
Reading off its entries gives
These are local formulas on a chosen branch: and have the same image, and at the origin the Jacobian matrix is singular, so this inverse-derivative formula does not apply there.
Apply the multivariable chain rule to a differentiable function on the chosen local branch of the parabolic coordinates:
Substituting part (ii) gives
For , the derivatives are and . Its endpoint values are and , so it satisfies both the ordinary differential equation and the boundary conditions. Moreover any solution of has the form ; the boundary conditions force and . Thus the unique solution of the boundary value problem is
The endpoint boundary conditions are
The finite difference equation can be written . Set . Then , so . Summing from to gives
Using and yields , hence . Therefore
This also covers , where there are no interior equations. Uniqueness follows because the difference of two solutions has zero second finite difference, hence is linear in , and vanishes at both endpoints. This is an exact finite difference solution for constant second derivative: the method is exact at the nodes here because the centered second finite difference differentiates this quadratic polynomial exactly.
The characteristic equation of the constant-coefficient linear ordinary differential equation is
whose roots of a polynomial are . Taking real and imaginary parts of the corresponding exponential functions gives the real general solution
For a particular solution, try . Substitution gives
Matching coefficients requires and , so and . Adding the homogeneous solution from part (i), the general solution is
Put . Substituting and into part (ii), using , gives
Thus and . Solving these two linear equations gives
Consequently the solution of the boundary value problem is
The two independent boundary conditions determine uniquely.
Since , divide by to obtain the first-order linear ordinary differential equation
An integrating factor is . Multiplication by this factor gives
After integration, , so
Let and . Subtracting the two constraint equations gives , hence and . The feasible set is therefore a circle.
For Lagrange multipliers , the stationarity equation becomes
At , the first equation gives . The second ensures and , so the third gives . The constraints then force . Both points do satisfy the multiplier equations, taking .
There are no missing singular constraint points: on the feasible circle, the two constraint gradients and are linearly independent, since . Thus the complete list of constrained critical points and critical values is
The bound on the feasible circle shows that the positive value is the global maximum and the negative value is the global minimum.
A function is periodic with period when
The period need not be the smallest positive one; for example, every positive integer multiple of a period is also a period.
Use the period-two Fourier series convention
Away from its jumps this square wave is an odd function, so . Its Fourier sine coefficients are
Only odd Fourier harmonics remain. Therefore
The Fourier series equals away from the jumps; at a jump it gives the midpoint of the one-sided limits by Dirichlet's theorem on Fourier series. The printed definition leaves the values at the integers unspecified. Choosing finite values there consistent with period two changes neither the Fourier coefficients nor these limiting values.
Figure 1.
Odd Fourier harmonics approximate the period-two square wave and vanish at every jump
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