For the normalized equations and on the positive quadrant,
is a first integral. It is nonnegative, strictly convex, and tends to infinity at the boundary and at infinity. Every positive regular level is therefore a compact simple closed curve traversed by one periodic orbit.
For the particular equation, write and . Its left side is . Choose and ; these are smooth invertible coordinates in the positive quadrant, with inverse , . In them and . Subtraction of their squares leaves , so the canonical equation is . Integrating it gives .
Parameterize the data curve by , . Its coordinate values are , so
Differentiate the first identity along the curve to get . Adding gives , and then . Thus for and for . Therefore
The coordinate rectangle gives exactly the region
Its boundary consists of up to and the ray from that point onward. It is unbounded upward. The original data curve lies inside this region. The sketch displays both characteristic boundaries and that data arc.
Figure 1.
Region fixed by the partial Cauchy data and its characteristic boundaries
. Details.
To establish the exact extent of uniqueness, outside this region either or . A smooth function supported in that unprescribed coordinate range can be added to or without changing either datum on the arc. Hence the displayed global formula is one extension, but data alone do not uniquely determine values outside the shaded region. Boundary values are fixed by continuity. The following classification criteria are pointwise and assume a nonzero principal coefficient matrix.
The equation is hyperbolic at a point when . The principal form has one positive and one negative eigenvalue and two distinct real characteristic directions. In the given equation , , , so throughout the positive quadrant, consistent with the two canonical characteristic families used above.
Let be prey and predator abundances. With constant positive demographic and predation coefficients, the Lotka-Volterra equations are
Their positive equilibrium is , . Its Jacobian matrix and eigenvalues are
The linearized populations oscillate with period , with the predator peak following the prey peak. This is a center equilibrium, not an attracting equilibrium. The conclusion is supported beyond linearization by the Logarithmic first integral of the Lotka-Volterra equations: in these units one may use
Direct differentiation gives . Its Hessian matrix is a positive-definite matrix in the positive quadrant, and its minimum is at . Nearby level curves are closed periodic orbits, so there is no damping toward a preferred oscillation amplitude.
For , take the Logarithmic first integral of the Lotka-Volterra equations
Along a trajectory,
Thus is a first integral. The scalar function is nonnegative for , vanishes only at , and tends to infinity as or . Moreover,
is positive definite, so is strictly convex. It follows that is its unique critical point and every level set is a compact smooth simple closed curve in the positive quadrant. The vector field is nonzero on such a level curve, so uniqueness of solutions makes each connected level curve one periodic orbit. The zero level consists of the fixed point . Hence every trajectory in is either periodic or the fixed point .
Use the Dulac theorem on the simply connected positive quadrant with . If , then
and hence
For , both terms have the same strict sign throughout . The Bendixson-Dulac criterion therefore gives no periodic orbit in . The same computation also excludes the case unless .
Set
Because the region lies in the positive quadrant, its four inequalities become
Thus this change of variables sends to a rectangle in the -plane. Its Jacobian determinant is
so
Since , the double integral is
Quadrant (plane geometry) Created 2026-10-14 Updated 2026-10-18
The two coordinate axes divide a Cartesian coordinate system in the plane into four open quadrants, distinguished by the signs of their coordinates. The positive quadrant is the first quadrant.