Multivariate Functions – Lecture 09

Review: Functions of one variable

  • Form: y=f(x)y = f(x)
    • One independent variable xx, one dependent variable yy.
  • Graph lives in Cartesian R2\mathbb R^2.
    • Horizontal axis: xx.
    • Vertical axis: yy.
  • Domain = set of permissible xx–values (interval(s) on the xx–axis).
  • Range = set of attained yy–values (interval(s) on the yy–axis).
  • Vertical–Line-Test (VLT): every vertical line intersects the graph at most once –necessary and sufficient condition for "single-valuedness" of ff.

Functions of two variables

  • General form: z=f(x,y)z = f(x,y).
    • Two independent variables (x,y)(x,y), one dependent variable zz.
  • Graph lives in R3\mathbb R^3.
    • Axes follow the Right-Hand Rule:
    • Fingers along +x+x, curl toward +y+y, thumb gives +z+z.
  • Domain = subset of the xyxy–plane (a 2-D region). Often written as a Cartesian product
    (x,y)[a,b]×[c,d](x,y) \in [a,b]\times[c,d].
  • Range = intervals on the zz–axis.
  • VLT still applies: a vertical line (parallel to the zz–axis) can meet the surface at most once.

"Usual Suspects" when finding domains

  • Square root: u    u0\sqrt{u}\;\Rightarrow\;u\ge 0.
  • Natural logarithm: \ln(u)\;\Rightarrow\;u>0.
  • Denominator: 1u    u0\dfrac{1}{u}\;\Rightarrow\;u\ne 0.

Worked domain examples (14.1.1 & 14.1.2)

(a) z=4x2y2z = \sqrt{4 - x^2 - y^2}

  • Condition: 4x2y20    x2+y244 - x^2 - y^2 \ge 0 \;\Rightarrow\;x^2 + y^2 \le 4.
  • Domain: closed disk of radius 22, centre at origin. Boundary circle x2+y2=4x^2+y^2=4 is included (solid line).
    • Sketch: shade the interior; label R=2R = 2.

(b) z=ln(4x+y2)z = \ln\bigl(4 - x + y^2\bigr)

  • Condition: 4 - x + y^2 > 0 \;\Rightarrow\;y^2 - x + 4 > 0.
  • Domain: open region to the right of the curved boundary y2x+4=0y^2 - x + 4 = 0 (dotted line excluded).
  • Quick test: point (0,0)(0,0) satisfies 4>0, so it belongs to the domain.
  • Boundary represents a sideways-opening parabola.

(c) Mixed "criss-cross, gaps & holes" example (14.1.2)

  • Function (implied by conditions): something like z=xy2y1z = \dfrac{ \sqrt{x-y^2}\,}{y-1}.
  • Combined restrictions
    • Square root: xy20    xy2x-y^2 \ge 0 \;\Rightarrow\;x \ge y^2 (region to the right of the parabola x=y2x=y^2, boundary mostly included).
    • Denominator: y10    y1y-1 \ne 0 \;\Rightarrow\;y \ne 1 (horizontal line y=1y=1 removed; shown as an open, dashed line).
  • Resulting domain: half-parabolic region xy2x \ge y^2 with a "gap" (hole) along y=1y=1. Interior contains points such as (4,0)(4,0); the point on the parabola at y=1y=1 is still excluded.

Identifying conic boundaries (visual tips)

  • x2+y2=r2x^2 + y^2 = r^2 Circle.
  • x2a2+y2b2=1\frac{x^2}{a^2}+\frac{y^2}{b^2}=1 Ellipse.
  • x2=4pyx^2 = 4py or y2=4pxy^2 = 4px Parabola.
  • x2y2=1x^2 - y^2 = 1 (or scaled) Hyperbola.
    • Recognising the boundary curve helps decide which side of it a domain occupies.

Level sets & contour lines (14.1)

  • Level set: collection of all domain points where f(x,y)=kf(x,y)=k for fixed constant kk.
    • For z=f(x,y)z=f(x,y) these appear as contour lines in the xyxy-plane.
  • Key facts
    • Each contour lives inside the domain.
    • Contours belonging to different kk values must not cross if the original surface is a function (otherwise one (x,y)(x,y) would yield two different zz-values).

Example 14.1.3

Function: f(x,y)=x2+y2=rf(x,y)=\sqrt{x^2+y^2}=r in polar coordinates.

  • Level values: k=0,1,2k=0,1,2.
  • Equations: x2+y2=k2x^2+y^2=k^2 circles of radius kk centred at origin.
  • Domain is all (x,y)(x,y) (no restrictions: inside/outside all circles acceptable).

Example 14.1.4

Function: f(x,y)=ey/xf(x,y)=e^{y/x}.

  • Domain: x0x\ne 0 (division by zero forbidden).
  • Requested levels: k=1,e,e2k=1,e,e^2.
  • Solve ey/x=k    y/x=lnk    y=(lnk)xe^{y/x}=k\;\Rightarrow\;y/x=\ln k \;\Rightarrow\;y=(\ln k)x.
    • k=1k=1: ln1=0y=0\ln 1=0\Rightarrow y=0 (the xx-axis, but x \ne 0).
    • k=ek=e: y=xy=x.
    • k=e2k=e^2: y=2xy=2x.
  • Each contour is a straight line through the origin; the line x=0x=0 is missing from the domain, so each level set has an infinitesimal gap at the origin.

Example 14.1.5

Function: f(x,y)=x+y+4f(x,y)=\sqrt{x+y+4}.

  • Domain condition: x+y+40yx4x+y+4\ge 0 \Rightarrow y\ge -x-4 (half-plane above this line; boundary included).
  • Levels: k=0,1,2,3k=0,1,2,3.
    • Square and rearrange: k2=x+y+4y=x+(k24)k^2=x+y+4\Rightarrow y=-x+(k^2-4).
    • Lines have slope m=1m=-1, vertical spacing Δb=(k<em>22k</em>12)\Delta b= (k<em>2^2-k</em>1^2).
  • Qualitative 3-D shape
    • Along any ray perpendicular to the domain boundary, zz increases like a square-root: steep near the boundary, shallower farther away.

Interpreting contour spacing

  • Draw contours at equal vertical intervals (Δz\Delta z constant).
    • Close contour lines large change in zz over small planar distance steep surface.
    • Widely spaced lines small gradient shallow slope.

Functions of three variables

  • Notation: w=T(x,y,z)w = T(x,y,z) (e.g.temperature inside a solid).
    • Domain: a 3-D region in R3\mathbb R^3 ("blob" of material, room, etc.).
  • Level surfaces ("isotherms" when TT is temperature): sets where T(x,y,z)=kT(x,y,z)=k.
    • Examples: T=35C,50C,65C,80CT=35^{\circ}\mathrm C, 50^{\circ}\mathrm C, 65^{\circ}\mathrm C, 80^{\circ}\mathrm C.
    • Each level surface is a 2-D sheet inside the 3-D domain.
  • As with contours, densely packed level surfaces indicate regions of large spatial temperature gradient.

Quick comparison table

  • 1-var: curve in R2\mathbb R^2, VLT, domain xx-intervals.
  • 2-var: surface in R3\mathbb R^3, VLT along zz-axis, domain planar regions, contour lines.
  • 3-var: hypersurface in R4\mathbb R^4 (visualised by level surfaces in R3\mathbb R^3).

Ethical & practical remarks (implicit)

  • Accurate domain identification prevents using formulas where they are undefined ( avoid dividing by zero, complex logs, etc.).
  • Contour/level-set reading underpins practical tools: topographic maps, weather isotherms, medical CT/isodose plots.
  • Understanding steepness via contour density links directly to gradient vectors and optimisation (topics that follow).