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For positive $m,n$, this mutual repression system can display bistability for some $\lambda$ exactly when both $m>1$ and $n>1$. If either exponent is at most one, it has a unique stable equilibrium for every $\lambda$. To prove the less obvious case $m\le 1<n$, put $a=x/(1+x)$ and $b=y/(1+y)$ at equilibrium. Equality of the two expressions for $\lambda$ gives $a\le b(1-b{)}^{n-1}$. The loop gain is then bounded by $mn{b}^2(1-b{)}^{n-1}$, whose maximum is $4mn(n-1{)}^{n-1}/(n+1{)}^{n+1}<1$. Swap the two components for the other case. If both exponents exceed one, sufficiently large $\lambda$ yields two stable equilibria with $(x,y)\sim (\lambda ,{\lambda }^{1-m})$ and $(x,y)\sim ({\lambda }^{1-n},\lambda )$. The weaker condition $mn\le 1$ is sufficient to exclude multistability, but does not exhaust all exclusions when the same production prefactor is imposed.

// Target: mathematical-biology.bigb

Assume the decreasing functions are continuously differentiable so their local gains are defined. In the positive quadrant, the nullclines are $x=f(y)$ and $y=g(x)$, both decreasing. The phase plane arrows point right when $x<f(y)$ and left when $x>f(y)$; they point up when $y<g(x)$ and down when $y>g(x)$. Both axes point into the quadrant. Since $f,g$ are bounded, sufficiently large $x$ or $y$ decreases, giving a bounded forward-invariant rectangle containing all equilibria and eventually containing each trajectory. Thus mutual repression can have one attracting intersection or several intersections separating different basins of attraction.

An equilibrium obeys $x_{\ast }=f(y_{\ast })$, $y_{\ast }=g(x_{\ast })$. Its Jacobian matrix and eigenvalues areThe product is nonnegative. Hence an intersection is a stable equilibrium with two negative real eigenvalues when $f^{\prime }{g}^{\prime }<1$, a saddle equilibrium when $f^{\prime }{g}^{\prime }>1$, and nonhyperbolic when $f^{\prime }{g}^{\prime }=1$. This is the mutual repression stability criterion. To see why an intervening saddle normally accompanies multistability, eliminate $y$ and set $F(x)=f(g(x))-x$. Bounded positivity gives $F(0)>0$ and $F(x)<0$ for large $x$, whileTwo downward, stable crossings require an upward crossing between them. For simple roots that middle crossing has $f^{\prime }{g}^{\prime }>1$ and is a saddle equilibrium. Its stable manifold separates the attracting states. Thus robust multistability requires the loop gain to exceed one at an intervening equilibrium, with the stable equilibria themselves having gain below one. A tangency at gain one is the threshold where equilibria can merge; degenerate crossings require higher-order analysis. A gain exceeding one somewhere is necessary for multiple intersections, but by itself does not prove that a particular pair of nullclines has multiple stable intersections.

Define the logarithmic repression sensitivitiesBoth are negative. At equilibrium $f(y_{\ast })=x_{\ast }$ and $g(x_{\ast })=y_{\ast }$, so their product is exactly $f^{\prime }(y_{\ast })g^{\prime }(x_{\ast })$. The condition can therefore be expressed asEquivalently, the product of the magnitudes of the two negative logarithmic gains must exceed one at that saddle equilibrium. The divergence of the vector field is identically $-2$, so the Bendixson-Dulac criterion excludes periodic orbits in the positive quadrant. The relevant stable long-time states in this bounded phase plane are thus equilibria, rather than attracting limit cycles. The following sketches illustrate the single-attractor and two-attractor possibilities; the saddle in the second panel lies on the diagonal, with its stable diagonal separating the two basins.