An Approach to Conic Sections

Size: px
Start display at page:

Download "An Approach to Conic Sections"

Transcription

1 n pproach to Conic ections Jia. F. Weng Introduction. The study of conic sections can be traced back to ancient Greek atheaticians, usually to pplonious (ca bc) [2]. The nae conic section coes fro the fact that the principle types of conic sections, known as ellipses, hyperbolas and parabolas, are generated by cutting a cone with a plane. However, ost odern textbooks on calculus depart fro this geoetric approach. Instead, conic sections are defined as soe types of loci and studied through analytic geoetry. In this paper we show a new approach to conic sections which are defined as the intersections of two cones. Then the vertices of two cones becoe the inherent foci of the conic section and a directrix exists associated with each of the inherent foci. ll known properties of conic sections still hold for the inherent foci and their associated directrixes in this new approach. Moreover, when a conic section and its foci and directrixes in space are projected to a horizontal plane, they becoe the ones discussed in planar analytic geoetry. This new approach sees sipler and ore natural than the classical geoetric and analytic approaches in defining conic sections and proving their properties. In the last section we show an application of the new approach in the network design in ining industry. In ppendix we derive the standard equation of a conic section with respect to the foci, lying on the cutting plane and referred to as the coplanar foci of the conic section. The author does not know any textbook that gives such a derivation. 2 Intersections of Two Right Circular Cones. Let x P, y P, z P denote the Cartesian coordinates of a point P. uppose P and Q are two distinct points. The length of line segent P Q is denoted by l(p Q), and the gradient of P Q is denoted by g(p Q) which is defined as g(p Q) z Q z P (x Q x P ) 2 + (y Q y P ) 2. (1) Let C(P ; ) denote a (double-napped) right circular cone whose vertex is P and whose generating lines have gradient ( > 0). The angle β fored by the axis of C(P ; ) and the generating lines is referred to as the generating angle of the cone. Clearly, tan β 1/. Now suppose and are two distinct points in space. The intersection of cones C(; ) and C(; ) is denoted by C(, ; ). ssue the horizontal distance between and is 2u while the vertical distance between and is 2h. Then, after a transforation we ay assue (u, 0, h), ( u, 0, h), u 0, h 0 (Fig. 1). Hence the equations describing C(; ) and C(; ) are (x u) 2 + y 2 (z h)2 2, (x + u) 2 + y 2 (z + h)2 2. (2) If h 0, then the intersection C(, ; ) lies trivially in the Y Z-plane. ssue h 0. ubtracting the first equation fro the second, we have z 2 u h x 2 x, (3) k

2 V Z R 2 O R 1 Y α β V P ~ Z Y O V V R 1 O V V V V R2 (1) (2) Figure 1: Intersections of two cones. where k h/u g(). It follows that C(, ; ) lies on a plane P which contains the Y -axis and eets the Y -plane at an angle α, referred to as the intersecting angle of two cones. We call this planar curve C(, ; ) a conic section, or siply a conic. In particular, if g(), C(, ; ) is a closed curve and called an ellipse (Fig. 1(1)); if g(), C(, ; ) has two separate branches, called a hyperbola (Fig. 1(2)). Trivially, in their degenerate cases in which g(), an ellipse becoes a line segent, and a hyperbola becoes two half-lines that are the extensions of. Moreover, there are two special cases: 1. If, lie in a vertical line, then g() and the ellipse is a circle lying in a horizontal plane. 2. If, lie in a horizontal plane, then g() 0 and the hyperbola lies in a vertical plane. ubstituting z with the right side of (3), fro (2) we obtain Hence the paraetric expression of C(, ; ) is ( y ± 2 u 2 h 2 )( 2 x 2 h 2 ). (4) h ( ( x, ± 2 u 2 h 2 )( 2 x 2 h 2 ), h ) 2 u h x. (5) Let V and V be the intersections of C(, ; ) with the Z-plane that are close to and respectively (Fig. 1). Then by Equations (3) and (4) V ( h, 0, u), V ( h, 0, u). (6) 2

3 Clearly, C(, ; ) is syetric with respect to two orthogonal lines: V V and the Y -axis. Therefore, O is the center of the conic section C(, ; ). When C(, ; ) is an ellipse, let R 1 and R 2 be the intersections of C(, ; ) with the positive and negative Y -axis respectively. Then again fro Equation (4) we find ( R 1 0, u ) ( k 2 2, 0, R 2 0, u ) k 2 2, 0. (7) When C(, ; ) is a hyperbola, (7) also defines two points on the Y -axis. In the case of an ellipse, V V is called the ajor axis while R 1 R 2 is called the inor axis of the ellipse. In the case of a hyperbola, V V is called the transverse axis while R 1 R 2 is called the conjugate axis of the hyperbola. Fro Equations (4) and (3), it is easy to derive that y x ±( 2 /k 2 1)x/y, z x 2 /k. Therefore, the tangent vector t of the conic section C(, ; ) is ( t 1, ±( 2 k 2 1)x y, 2 ). (8) k Reark 1 Note t is copletely deterined by and k, independent fro the coordinates of and. Now suppose C(, ; ) is a hyperbola. When x goes to infinity, by (4) y/x goes to 2 /k 2 1 and the tangent vector becoes t 0, ± 2 2 1,. k2 k The two lines through O in the directions of t are the asyptotes of the hyperbola, which lie in the plane P where the hyperbola lies. Conic sections have two iportant properties: constant su/difference property and reflective property. First we prove a lea [5]. Lea 2 uppose the endpoint of a line is perturbed in direction v. Let the angle between and v be θ. Then the directional derivative of l() with respect to v is ( cos θ). Proof: uppose oves to in direction v. Let l 0 l(), l l( ), ε l( ). Then l 2 l ε2 2εl 0 cos θ, and 2l dl 2(ε l 0 cos θ) dε. Note l l 0 when ɛ 0. Therefore The lea is proved. l v dl li cos θ. ε 0 dε Theore 3 (constant su/difference) For any point on an ellipse C(, ; ), the su of the distances fro to the vertices and is constant. For any point on a hyperbola C(, ; ), the difference of the distances fro to the vertices and is constant. 3

4 Proof: There is no loss of generality that we assue (u, 0, h), ( u, 0, h) as before. ecause g() g(), when k and C(, ; ) is an ellipse, l() + l() ( Z Z + Z Z ) 2h The arguent is siilar for the case of C(, ; ) being a hyperbola. This property copletely characterizes ellipses and hyperbolas, therefore, we can redefine ellipses/hyperbolas to be planar curves that satisfy the constant su/difference property. That is, an ellipse (or a hyperbola) is a planar curve such that the su (or difference respectively) of the distances between any point on the curve and two fixed distinct points is constant. This property iplies another property which is iportant in applications of conic sections. Corollary 4 (reflection) For any point on an ellipse or a hyperbola, the tangent line at eets and at the sae acute angle. Proof: Let the acute angle between t and, be θ, φ respectively. y Lea 2, l t() cos θ, l t() cos(π φ) cos φ. For an ellipse, since l() + l() is constant, l t() + l t() cos θ + cos φ 0. Hence θ φ. The arguent is siilar for hyperbolas. Reark 5 This corollary can also be proved by Equation (8). ecause of the reflective property and are called the inherent foci of C(, ; ). Let Ā, and C(Ā, ) be the projections of, and C(, ; ) on a horizontal plane respectively. Then any point on C(Ā, ) is the projection of certain point on C(, ; ). ecause l(ā ) ± l( ) (l() ± l()) sin β const, C(Ā, ) is also an ellipse or a hyperbola with foci Ā and. ince Ā and lie on the sae plane where the curve C(Ā, ) lies, we call the coplanar foci of the curve. Moreover, let V, V, R 1 and R 2 be the projections of V, V, R 1 and R 2 on the sae plane respectively. Then V V and R 1 R2 are the ajor and inor axes (or the transverse and conjugate axes) of the ellipse (or the hyperbola respectively) C(Ā, ). The equation of C(Ā, ) can be easily derived fro Equation (4) as follows: where x 2 ā 2 + y2 b2 1, (9) ā 2 h2 2, b 2 h2 2 u 2 2 (k2 2 )u 2 2. (10) Equation (9) is called the standard for of an ellipse or a hyperbola, depending on b 2 0 or b 2 0, i.e. on k or k. Note that 2ā l( V V ), 2 b l( R 1 R2 ). Let 2 c l(ā ) 2u. Then it is easy to see that c 2 ā 2 b 2, if C(Ā, ) is an ellipse, c 2 b 2 ā 2, if C(Ā, ) is a hyperbola. 4

5 Figure 2: Confocal ellipses and hyperbolas. 3 Confocal and iilar Conics, Parabolas. The shape of a conic section is copletely deterined by two paraeters and k. investigate how the curve varies as or k changes. Now we (1) If and are fixed, i.e. k is fixed, but changes, we obtain a faily of conics that lie on different planes but share, as their coon foci. These conics are called confocal. s argued above, when these curves are projected to the sae horizontal plane, their projections are also confocal with Ā, as their coon foci (Fig. 2, based on a figure in [3]). (2) Now we study how C(, ; ) varies if is fixed but k changes. Without loss of generality we assue is fixed and oves to that lies in the sae vertical plane. Let (u+ε, 0, h+ δ), ε 0, δ 0. Then the equations of cones C( ; ) and C(; ) becoe (x u ε) 2 + y 2 (z h δ)2 2, (x + u) 2 + y 2 (z + h)2 2. (11) Of all possible oves of we discuss the oves in three special directions: along, horizontal and along V. (2.1) ove of either preserves the gradient between two cone vertices or does not. If it does, then δ/ε h/u k. olving the syste (11) with δ kε we have z 2 k x + (h2 2 u 2 )ε. 2hu Therefore, the new conic section C(, ; ) lies in a plane P that is parallel to the plane P where C(, ; ) lies. esides, since both curves lie on the sae cone C(; ), it follows that the two conics C(, ; ) and C(, ; ) are siilar relative to their coon focus. When projected on the sae horizontal plane, their projections are also siilar relative to (Fig.??). On the other hand, if the ove of does not preserve the gradient between the vertices, then P is not parallel to P, and C(, ; ) is not siilar to C(, ; ) by the definition of siilarity. 5

6 Z Y * P ~ L V O D D L V Y Figure 3: parabola as an extree ellipse. Reark 6 curve C 1 (x 1 (t), y 1 (t), z 1 (t)) is said to be siilar to another curve C 2 (x 2 (t), y 2 (t), z 2 (t)) relative to point (x 0, y 0, z 0 ) if x 2 (t) x 0 x 1 (t) x 0 y 2(t) y 0 y 1 (t) y 0 z 2(t) z 0 z 1 (t) z 0. (2.2) The vertex oves in the direction of the positive -axis, that is, δ 0 and ε onotone increases. ssue we start with g() k > and the conic is an ellipse. In this ove, the ellipse C(, ; ) becoes narrower and narrower, and finally becoes a line segent, a degenerate ellipse with k (h + δ)/(u + ε). If the increase of ε continues, then as stated in ection 2, the line segent first suddenly jups into two half-lines as a degenerate hyperbola, and then becoes a noral hyperbola with k <. (2.3) s we have discussed in (2.2), in the degenerate case, an ellipse or a hyperbola overlaps the line through and. One ay ask if there is a non-degenerate coon extree of ellipses and hyperbolas. Look at the ove of along V. In such a ove δ ε. olving the syste (11) with δ ε and then let ε go to infinity, we have y ± 2 (h u)(x + h), z (x u) + h. (12) Therefore the paraetric expression of the resulting curve is ( x, ± 2 ) (h u)(x + h), (x u) + h. (13) 6

7 If starting with a hyperbola (h/k < ), we obtain the sae result. Therefore, the resulting planar curve, called a parabola, is the non-degenerate coon extree of ellipses and hyperbolas. The parabola has a vertex V and is syetric about the line V, the intersection of P and the Z-plane. Let L {( 2h + u, y, h)} be the point set that is the intersection of the plane P and the horizontal plane through (Fig. 3). For any point on the parabola, let D be the foot of the perpendicular fro to L. Then the gradient of D is the slope of the plane P, which is equal to the gradient of any generating line of C(; ). Therefore, siilarly to the arguent for ellipses and hyperbolas, we have l() l(d). Theore 7 (equidistance) For any point on the parabola, the distance fro to equals the distance fro to the line L. For this reason, is called the inherent focus of the hyperbola, and L is called the directrix associated with the inherent focus. s ellipses and hyperbolas, this equidistance property copletely characterizes parabolas and we can redefine a parabola to be a planar curve that satisfies the equidistance property. The ratio of the distance fro to the focus to the distance fro to the directrix is called the eccentricity of the parabola. Thus, a parabola can also be defined as a planar curve whose eccentricity is one. gain, the equidistance property iplies the reflective property: Corollary 8 (reflection of parabolas) For any point on a parabola, the tangent line t at eets two lines at the sae acute angle: the line joining and the focus and the perpendicular fro to the directrix. Now denote the parabola by C(, L; ). Let C(, L), V,,, L and D be the projections of C(, L; ), V,,, L and D on a horizontal plane respectively. ecause and D have the sae gradient, l() l(d) iplies l( ) l( D). Therefore, the projection C(, L) is also a parabola, whose coplanar focus is and the directrix associated with is L. Fro (12) the equation of C(, L) is y 2 4 p(x + h/), where p h/ u is the distance fro the vertex V to the coplanar focus or to the directrix L. This equation is the standard for of a parabola with vertex at ( h/, 0). If the origin oves to the vertex V, then the equation is further siplified to y 2 4px. 4 Discussions (1) It is easy to see that any ellipse (or hyperbola) C obtained by cutting a cone with a plane can be generated by two cones. Factually, we ay assue that the cone C is C(; ). Then ake a copy of C(; ) and turn the copy 180 around the Y -axis, the copy becoes the required C(; ). (2) s parabolas, an ellipse or a hyperbolas has two directrixes associated with its inherent foci and : They are the intersections of P and the horizontal planes through and. Figure 4(1) shows the directrix L of an ellipse C(, ; ) associated with. For any point on the ellipse, let D be the foot of the perpendicular fro to L. The eccentricity of the conic section C(, ; ) is still defined to be the ratio of l() to l(d). Let H be the foot of the perpendicular 7

8 Z O Y α β F V P ~ Z Y * P ~ D L α L ~ V F C β H L L ~ F O C (1) (2) Figure 4: Coplanar foci and their directrixes. fro to the horizontal plane through. ince H equals the generating angle β, and HD equals the intersecting angle α (Fig. 4(1)), When projected to a horizontal plane, l( ) l( l() l(h)/ cos β l(d) l(h)/ sin α sin α cos β D) l(h) l(dh) const < 1. l(h)/ cot β l(h)/ tan α tan α const < 1. cot β Thus, the third definition of ellipses is that an ellipse is a planar curve whose eccentricity is a constant less than one. These arguent can be siilarly apply to hyperbolas. Hence, the third definition of hyperbolas is that a hyperbola is a planar curve whose eccentricity is a constant greater than one. (3) Finally we should point out that an ellipse or a hyperbola C(, ; ) also has its own coplanar foci lying on the plane P. Take an ellipse as an exaple. ccording to Quetelet-Dandelin s construction [2], suppose the sphere inscribing C(; ) and P touches P at a point F. Then F is a coplanar focus of C(, ; ). nother focus F can be found in a siilar way. ssociated with these coplanar foci, there are two directrixes. For instance, suppose the sphere defined above touches the cone C(; ) at a horizontal circle C (Fig. 4(1)). Then the intersection of P and the plane through C is the directrix L associated with the focus F. In a siilar way we can find the coplanar focus F and its associated directrix L for a parabola C(, L; ) (Fig. 4(2)). The coordinates of the coplanar foci and the standard equations of conic sections with respect to its coplanar foci and directrixes are derived in ppendix. 5 n application. Given a point set, the iniu network proble asks for a network of shortest total length interconnecting all given points. To shorten the network, probably soe points not in the given 8

9 deposit ground deposit C Figure 5: ining network. point set are added. In the literature this iniu network is called a teiner inial tree and the additional points are called teiner points [4]. The teiner tree proble was first posed by Ferat who asked how to find the point in a triangle C so that the su of the distances fro to the vertices,, and C is inial [4]. There are any generalizations of the teiner tree proble. recently studied one is the gradient-constrained teiner tree proble [1]. Figure 5 depicts a siple exaple of an underground ining network in which the ore in two deposits is extracted through tunnels to a vertical shaft and then hauled up to the ground. In the figure and are two prescribed access points in deposits. In practice, the gradient of any tunnel cannot be very steep. The typical axiu gradient is about 1:7. In this exaple we need to find a point so that with this gradient constraint the total length of the network f l()+l()+l(c) is iniized, where C is the access point to be deterined on the vertical shaft. Clearly, to iniize f, C should be perpendicular to the vertical shaft. Hence, C is horizontal and autoatically satisfies the gradient constraint. It can be shown that if g() >, then and ust have the axial gradient in order to iniize f [6]. It follows that lies on the ellipse C(, ; ), and that C C because of the reflective property. These conditions copletely deterine and C. References [1] M.razil, D..Thoas and J.F.Weng, Gradient-constrained inial teiner trees, DIMC eries in Discrete Matheatics and Theoretical Coputer cience, Vol. 40 (1998), pp [2] J.L.Coolidge, history of the conic sections and quadric surfaces, Oxford University Press, London, [3] R.Courant and H.Robbis, What is atheatics? Oxford University Press, London, [4] F.K.Hwang, D..Richard and P.Winter, The teiner tree proble, North-Holland, [5] J.H.Rubinstein and D..Thoas, variational approach to the teiner network proble, nn. Oper. Res., Vol. 33 (1991), pp [6] J.F.Weng, note on constrained shortest connections of two points to a vertical line, preprint. 9

10 ppendix. If C(, ; ) is an ellipse, then let F and F be a pair of points lying on V V and syetric to O such that 0 ρ l(of )/l(ov ) 1. iilarly, if C(, ; ) is a hyperbola, then define F and F be the points lying on the extension of V V and syetric to O such that ρ l(of )/l(ov ) > 1. y the definition ( ) ρh F, 0, ρu, F ( ρh ), 0, ρu. (14) Let (x, y, z) be a point on C(, ; ), then l 1 l(f ) l 2 l(f ) (ρh (ρh x ) 2 + y 2 + (ρu z) 2, + x ) 2 + y 2 + (ρu + z) 2. Let l 1 ± l 2 2ã, ã 0. Then l 2 1 (2ã l 2) 2, l 2 1 l2 2 4ã2 4ãl 2, ±ãl 2 ã 2 l2 1 l2 2 4 quaring both sides, after a siplification we obtain ã 2 + ρhx + ρuz. (h 2 ρ 2 2 ã 2 )x huρ 2 xz + ( 2 u 2 ρ 2 ã 2 ) 2 z 2 2 ã 2 y 2 ( 4 u 2 + h 2 )ã 2 ρ 2 + ã ubstituting y and z with (4) and (3) respectively, finally we have an equation containing only one variable x: f 1 x 2 + f 2 0, (15) where f 1 4 u 2 (1 + 2 )ã 2 (h u 2 ) 2 ρ 2, f 2 h 2 (h 2 2 u 2 )ã 2 2 h 2 ã 4 + h 2 (h u 2 )ã 2 ρ 2. Equation (15) will hold for any x if both f 1 0 and f 2 0. olving this syste we obtain h ã u 2, ρ u ã Thus, the constant su/difference of distances and the coordinates of the coplanar foci F, F are both deterined. y the definition of the intersecting angle α, we have cos α h/(ã), sin α u/ã. fter an anticlockwise rotation of the coordinate syste around the Y -axis by α, let the new axes be O, OỸ and O Z. Then the Ỹ -plane is the plane P where the conic section lies. ince the curve lies on the Ỹ -plane, we have z 0, and the the transforation is x x cos α, y ỹ, z x sin α. Fro (4) we can derive the standard for of the conic section on the plane P: ( x) 2 (ã) 2 + (ỹ)2 1, (16) ( b) 2 10

11 where b 2 (h 2 / 2 ) u 2. Note b 2 0 when g() and the conic section is an ellipse, and b2 0 when g() and the conic section is a hyperbola. It is easy to check ã l(ov ), b l(or 1 ). Let c l(of ). Then as in the projection of C(, ; ), the following equations hold: c 2 ã 2 b 2, if C(, ; ) is an ellipse, c 2 b 2 ã 2, if C(, ; ) is a hyperbola. In the sae way we can deterine the coplanar focus F and its directrix L for a parabola. s shown in Figure 4(2), let ρ be the horizontal distance between V and F. ince the gradient of V F is and since V has the sae distance to F and to L, we have F (ρ h ) (, 0, (ρ u), L ρ h ), y, (ρ + u). uppose (x, y, z) is a point on the parabola. Then the square of l(f ) equals the square of the distance fro to L, ( x ρ + ) h ( ) 2 2 ( + y 2 + z ρ2 h + u x + ρ + ) h ( ) z + ρ2 h + u. ecause y and z satisfy (12), this equation always holds if ρ h u (1 + 2 ). Note now cos α 1/ s argued in the case of ellipses and hyperbolas, after an anticlockwise rotation of the coordinate syste by α, fro (12) we obtain the standard for of the parabola on the plane P: ỹ 2 4 p( x + h ), (17) where p 4(h u)/( ) and h / l(v F ). If the origin oves to V, then it can be further siplified to ỹ 4 p x. 11

The Distance Formula. The Midpoint Formula

The Distance Formula. The Midpoint Formula Math 120 Intermediate Algebra Sec 9.1: Distance Midpoint Formulas The Distance Formula The distance between two points P 1 = (x 1, y 1 ) P 2 = (x 1, y 1 ), denoted by d(p 1, P 2 ), is d(p 1, P 2 ) = (x

More information

Chapter 6 1-D Continuous Groups

Chapter 6 1-D Continuous Groups Chapter 6 1-D Continuous Groups Continuous groups consist of group eleents labelled by one or ore continuous variables, say a 1, a 2,, a r, where each variable has a well- defined range. This chapter explores:

More information

Circles. Example 2: Write an equation for a circle if the enpoints of a diameter are at ( 4,5) and (6, 3).

Circles. Example 2: Write an equation for a circle if the enpoints of a diameter are at ( 4,5) and (6, 3). Conics Unit Ch. 8 Circles Equations of Circles The equation of a circle with center ( hk, ) and radius r units is ( x h) ( y k) r. Example 1: Write an equation of circle with center (8, 3) and radius 6.

More information

Least Squares Fitting of Data

Least Squares Fitting of Data Least Squares Fitting of Data David Eberly, Geoetric Tools, Redond WA 98052 https://www.geoetrictools.co/ This work is licensed under the Creative Coons Attribution 4.0 International License. To view a

More information

Conic Sections. Geometry - Conics ~1~ NJCTL.org. Write the following equations in standard form.

Conic Sections. Geometry - Conics ~1~ NJCTL.org. Write the following equations in standard form. Conic Sections Midpoint and Distance Formula M is the midpoint of A and B. Use the given information to find the missing point. 1. A(, 2) and B(3, -), find M 2. A(5, 7) and B( -2, -), find M 3. A( 2,0)

More information

12 th Annual Johns Hopkins Math Tournament Saturday, February 19, 2011 Power Round-Poles and Polars

12 th Annual Johns Hopkins Math Tournament Saturday, February 19, 2011 Power Round-Poles and Polars 1 th Annual Johns Hopkins Math Tournaent Saturday, February 19, 011 Power Round-Poles and Polars 1. Definition and Basic Properties 1. Note that the unit circles are not necessary in the solutions. They

More information

Distance and Midpoint Formula 7.1

Distance and Midpoint Formula 7.1 Distance and Midpoint Formula 7.1 Distance Formula d ( x - x ) ( y - y ) 1 1 Example 1 Find the distance between the points (4, 4) and (-6, -). Example Find the value of a to make the distance = 10 units

More information

3. A( 2,0) and B(6, -2), find M 4. A( 3, 7) and M(4,-3), find B. 5. M(4, -9) and B( -10, 11) find A 6. B(4, 8) and M(-2, 5), find A

3. A( 2,0) and B(6, -2), find M 4. A( 3, 7) and M(4,-3), find B. 5. M(4, -9) and B( -10, 11) find A 6. B(4, 8) and M(-2, 5), find A Midpoint and Distance Formula Class Work M is the midpoint of A and B. Use the given information to find the missing point. 1. A(4, 2) and B(3, -8), find M 2. A(5, 7) and B( -2, -9), find M 3. A( 2,0)

More information

MA304 Differential Geometry

MA304 Differential Geometry MA304 Differential Geoetry Hoework 4 solutions Spring 018 6% of the final ark 1. The paraeterised curve αt = t cosh t for t R is called the catenary. Find the curvature of αt. Solution. Fro hoework question

More information

About the definition of parameters and regimes of active two-port networks with variable loads on the basis of projective geometry

About the definition of parameters and regimes of active two-port networks with variable loads on the basis of projective geometry About the definition of paraeters and regies of active two-port networks with variable loads on the basis of projective geoetry PENN ALEXANDR nstitute of Electronic Engineering and Nanotechnologies "D

More information

Solutions of some selected problems of Homework 4

Solutions of some selected problems of Homework 4 Solutions of soe selected probles of Hoework 4 Sangchul Lee May 7, 2018 Proble 1 Let there be light A professor has two light bulbs in his garage. When both are burned out, they are replaced, and the next

More information

International Mathematical Olympiad. Preliminary Selection Contest 2009 Hong Kong. Outline of Solutions

International Mathematical Olympiad. Preliminary Selection Contest 2009 Hong Kong. Outline of Solutions International Matheatical Olypiad Preliinary Selection ontest 009 Hong Kong Outline of Solutions nswers:. 03809. 0 3. 0. 333. 00099 00. 37 7. 3 8. 3 9. 3 0. 8 3. 009 00. 3 3. 3. 89. 8077. 000 7. 30 8.

More information

2.003 Engineering Dynamics Problem Set 2 Solutions

2.003 Engineering Dynamics Problem Set 2 Solutions .003 Engineering Dynaics Proble Set Solutions This proble set is priarily eant to give the student practice in describing otion. This is the subject of kineatics. It is strongly recoended that you study

More information

yields m 1 m 2 q 2 = (m 1 + m 2 )(m 1 q m 2 q 2 2 ). Thus the total kinetic energy is T 1 +T 2 = 1 m 1m 2

yields m 1 m 2 q 2 = (m 1 + m 2 )(m 1 q m 2 q 2 2 ). Thus the total kinetic energy is T 1 +T 2 = 1 m 1m 2 1 I iediately have 1 q 1 = f( q )q/ q and q = f( q )q/ q. Multiplying these equations by and 1 (respectively) and then subtracting, I get 1 ( q 1 q ) = ( + 1 )f( q )q/ q. The desired equation follows after

More information

3. A( 2,0) and B(6, -2), find M 4. A( 3, 7) and M(4,-3), find B. 5. M(4, -9) and B( -10, 11) find A 6. B(4, 8) and M(-2, 5), find A

3. A( 2,0) and B(6, -2), find M 4. A( 3, 7) and M(4,-3), find B. 5. M(4, -9) and B( -10, 11) find A 6. B(4, 8) and M(-2, 5), find A Midpoint and Distance Formula Class Work M is the midpoint of A and B. Use the given information to find the missing point. 1. A(, 2) and B(3, -8), find M 2. A(5, 7) and B( -2, -), find M (3. 5, 3) (1.

More information

January 21, 2018 Math 9. Geometry. The method of coordinates (continued). Ellipse. Hyperbola. Parabola.

January 21, 2018 Math 9. Geometry. The method of coordinates (continued). Ellipse. Hyperbola. Parabola. January 21, 2018 Math 9 Ellipse Geometry The method of coordinates (continued) Ellipse Hyperbola Parabola Definition An ellipse is a locus of points, such that the sum of the distances from point on the

More information

Poornima University, For any query, contact us at: , 18

Poornima University, For any query, contact us at: , 18 AIEEE//Math S. No Questions Solutions Q. Lets cos (α + β) = and let sin (α + β) = 5, where α, β π, then tan α = 5 (a) 56 (b) 9 (c) 7 (d) 5 6 Sol: (a) cos (α + β) = 5 tan (α + β) = tan α = than (α + β +

More information

Conchoid surfaces of spheres

Conchoid surfaces of spheres Conchoid surfaces of spheres Martin Peternell a, David Gruber a, Juana Sendra b a Institute of Discrete Matheatics and Geoetry, Vienna University of Technology, Austria. b Dpto. Mateática Aplicada a I.T.

More information

Least squares fitting with elliptic paraboloids

Least squares fitting with elliptic paraboloids MATHEMATICAL COMMUNICATIONS 409 Math. Coun. 18(013), 409 415 Least squares fitting with elliptic paraboloids Heluth Späth 1, 1 Departent of Matheatics, University of Oldenburg, Postfach 503, D-6 111 Oldenburg,

More information

Feature Extraction Techniques

Feature Extraction Techniques Feature Extraction Techniques Unsupervised Learning II Feature Extraction Unsupervised ethods can also be used to find features which can be useful for categorization. There are unsupervised ethods that

More information

arxiv: v2 [math.ho] 28 May 2017

arxiv: v2 [math.ho] 28 May 2017 On the eleentary single-fold operations of origai: reflections and incidence constraints on the plane Jorge C. Lucero arxiv:1610.09923v2 [ath.ho] 28 May 2017 May 30, 2017 Abstract This article reviews

More information

Senior Math Circles February 11, 2009 Conics II

Senior Math Circles February 11, 2009 Conics II 1 University of Waterloo Faculty of Mathematics Centre for Education in Mathematics and Computing Senior Math Circles February 11, 2009 Conics II Locus Problems The word locus is sometimes synonymous with

More information

Polytopes and arrangements: Diameter and curvature

Polytopes and arrangements: Diameter and curvature Operations Research Letters 36 2008 2 222 Operations Research Letters wwwelsevierco/locate/orl Polytopes and arrangeents: Diaeter and curvature Antoine Deza, Taás Terlaky, Yuriy Zinchenko McMaster University,

More information

Model Fitting. CURM Background Material, Fall 2014 Dr. Doreen De Leon

Model Fitting. CURM Background Material, Fall 2014 Dr. Doreen De Leon Model Fitting CURM Background Material, Fall 014 Dr. Doreen De Leon 1 Introduction Given a set of data points, we often want to fit a selected odel or type to the data (e.g., we suspect an exponential

More information

TARGET QUARTERLY MATHS MATERIAL

TARGET QUARTERLY MATHS MATERIAL Adyar Adambakkam Pallavaram Pammal Chromepet Now also at SELAIYUR TARGET QUARTERLY MATHS MATERIAL Achievement through HARDWORK Improvement through INNOVATION Target Centum Practising Package +2 GENERAL

More information

QUESTION BANK ON. CONIC SECTION (Parabola, Ellipse & Hyperbola)

QUESTION BANK ON. CONIC SECTION (Parabola, Ellipse & Hyperbola) QUESTION BANK ON CONIC SECTION (Parabola, Ellipse & Hyperbola) Question bank on Parabola, Ellipse & Hyperbola Select the correct alternative : (Only one is correct) Q. Two mutually perpendicular tangents

More information

Solutions 1. Introduction to Coding Theory - Spring 2010 Solutions 1. Exercise 1.1. See Examples 1.2 and 1.11 in the course notes.

Solutions 1. Introduction to Coding Theory - Spring 2010 Solutions 1. Exercise 1.1. See Examples 1.2 and 1.11 in the course notes. Solutions 1 Exercise 1.1. See Exaples 1.2 and 1.11 in the course notes. Exercise 1.2. Observe that the Haing distance of two vectors is the iniu nuber of bit flips required to transfor one into the other.

More information

A NOTE ON HILBERT SCHEMES OF NODAL CURVES. Ziv Ran

A NOTE ON HILBERT SCHEMES OF NODAL CURVES. Ziv Ran A NOTE ON HILBERT SCHEMES OF NODAL CURVES Ziv Ran Abstract. We study the Hilbert schee and punctual Hilbert schee of a nodal curve, and the relative Hilbert schee of a faily of curves acquiring a node.

More information

Curious Bounds for Floor Function Sums

Curious Bounds for Floor Function Sums 1 47 6 11 Journal of Integer Sequences, Vol. 1 (018), Article 18.1.8 Curious Bounds for Floor Function Sus Thotsaporn Thanatipanonda and Elaine Wong 1 Science Division Mahidol University International

More information

Introduction to conic sections. Author: Eduard Ortega

Introduction to conic sections. Author: Eduard Ortega Introduction to conic sections Author: Eduard Ortega 1 Introduction A conic is a two-dimensional figure created by the intersection of a plane and a right circular cone. All conics can be written in terms

More information

arxiv: v1 [math.nt] 14 Sep 2014

arxiv: v1 [math.nt] 14 Sep 2014 ROTATION REMAINDERS P. JAMESON GRABER, WASHINGTON AND LEE UNIVERSITY 08 arxiv:1409.411v1 [ath.nt] 14 Sep 014 Abstract. We study properties of an array of nubers, called the triangle, in which each row

More information

Construction of the Electronic Angular Wave Functions and Probability Distributions of the Hydrogen Atom

Construction of the Electronic Angular Wave Functions and Probability Distributions of the Hydrogen Atom Construction of the Electronic Angular Wave Functions and Probability Distributions of the Hydrogen Ato Thoas S. Kuntzlean Mark Ellison John Tippin Departent of Cheistry Departent of Cheistry Departent

More information

Polygonal Designs: Existence and Construction

Polygonal Designs: Existence and Construction Polygonal Designs: Existence and Construction John Hegean Departent of Matheatics, Stanford University, Stanford, CA 9405 Jeff Langford Departent of Matheatics, Drake University, Des Moines, IA 5011 G

More information

In this chapter, we consider several graph-theoretic and probabilistic models

In this chapter, we consider several graph-theoretic and probabilistic models THREE ONE GRAPH-THEORETIC AND STATISTICAL MODELS 3.1 INTRODUCTION In this chapter, we consider several graph-theoretic and probabilistic odels for a social network, which we do under different assuptions

More information

The Lagrangian Method vs. other methods (COMPARATIVE EXAMPLE)

The Lagrangian Method vs. other methods (COMPARATIVE EXAMPLE) The Lagrangian ethod vs. other ethods () This aterial written by Jozef HANC, jozef.hanc@tuke.sk Technical University, Kosice, Slovakia For Edwin Taylor s website http://www.eftaylor.co/ 6 January 003 The

More information

Proc. of the IEEE/OES Seventh Working Conference on Current Measurement Technology UNCERTAINTIES IN SEASONDE CURRENT VELOCITIES

Proc. of the IEEE/OES Seventh Working Conference on Current Measurement Technology UNCERTAINTIES IN SEASONDE CURRENT VELOCITIES Proc. of the IEEE/OES Seventh Working Conference on Current Measureent Technology UNCERTAINTIES IN SEASONDE CURRENT VELOCITIES Belinda Lipa Codar Ocean Sensors 15 La Sandra Way, Portola Valley, CA 98 blipa@pogo.co

More information

a a a a a a a m a b a b

a a a a a a a m a b a b Algebra / Trig Final Exa Study Guide (Fall Seester) Moncada/Dunphy Inforation About the Final Exa The final exa is cuulative, covering Appendix A (A.1-A.5) and Chapter 1. All probles will be ultiple choice

More information

Geometry. Selected problems on similar triangles (from last homework).

Geometry. Selected problems on similar triangles (from last homework). October 30, 2016 Geoetry. Selecte probles on siilar triangles (fro last hoework). Proble 1(5). Prove that altitues of any triangle are the bisectors in another triangle, whose vertices are the feet of

More information

List Scheduling and LPT Oliver Braun (09/05/2017)

List Scheduling and LPT Oliver Braun (09/05/2017) List Scheduling and LPT Oliver Braun (09/05/207) We investigate the classical scheduling proble P ax where a set of n independent jobs has to be processed on 2 parallel and identical processors (achines)

More information

M ath. Res. Lett. 15 (2008), no. 2, c International Press 2008 SUM-PRODUCT ESTIMATES VIA DIRECTED EXPANDERS. Van H. Vu. 1.

M ath. Res. Lett. 15 (2008), no. 2, c International Press 2008 SUM-PRODUCT ESTIMATES VIA DIRECTED EXPANDERS. Van H. Vu. 1. M ath. Res. Lett. 15 (2008), no. 2, 375 388 c International Press 2008 SUM-PRODUCT ESTIMATES VIA DIRECTED EXPANDERS Van H. Vu Abstract. Let F q be a finite field of order q and P be a polynoial in F q[x

More information

Probability Distributions

Probability Distributions Probability Distributions In Chapter, we ephasized the central role played by probability theory in the solution of pattern recognition probles. We turn now to an exploration of soe particular exaples

More information

( 1 ) Find the co-ordinates of the focus, length of the latus-rectum and equation of the directrix of the parabola x 2 = - 8y.

( 1 ) Find the co-ordinates of the focus, length of the latus-rectum and equation of the directrix of the parabola x 2 = - 8y. PROBLEMS 04 - PARABOLA Page 1 ( 1 ) Find the co-ordinates of the focus, length of the latus-rectum and equation of the directrix of the parabola x - 8. [ Ans: ( 0, - ), 8, ] ( ) If the line 3x 4 k 0 is

More information

Intelligent Systems: Reasoning and Recognition. Perceptrons and Support Vector Machines

Intelligent Systems: Reasoning and Recognition. Perceptrons and Support Vector Machines Intelligent Systes: Reasoning and Recognition Jaes L. Crowley osig 1 Winter Seester 2018 Lesson 6 27 February 2018 Outline Perceptrons and Support Vector achines Notation...2 Linear odels...3 Lines, Planes

More information

arxiv: v1 [cs.ds] 3 Feb 2014

arxiv: v1 [cs.ds] 3 Feb 2014 arxiv:40.043v [cs.ds] 3 Feb 04 A Bound on the Expected Optiality of Rando Feasible Solutions to Cobinatorial Optiization Probles Evan A. Sultani The Johns Hopins University APL evan@sultani.co http://www.sultani.co/

More information

A Better Algorithm For an Ancient Scheduling Problem. David R. Karger Steven J. Phillips Eric Torng. Department of Computer Science

A Better Algorithm For an Ancient Scheduling Problem. David R. Karger Steven J. Phillips Eric Torng. Department of Computer Science A Better Algorith For an Ancient Scheduling Proble David R. Karger Steven J. Phillips Eric Torng Departent of Coputer Science Stanford University Stanford, CA 9435-4 Abstract One of the oldest and siplest

More information

Chapter 1 Analytic geometry in the plane

Chapter 1 Analytic geometry in the plane 3110 General Mathematics 1 31 10 General Mathematics For the students from Pharmaceutical Faculty 1/004 Instructor: Dr Wattana Toutip (ดร.ว ฒนา เถาว ท พย ) Chapter 1 Analytic geometry in the plane Overview:

More information

Research Article Approximate Multidegree Reduction of λ-bézier Curves

Research Article Approximate Multidegree Reduction of λ-bézier Curves Matheatical Probles in Engineering Volue 6 Article ID 87 pages http://dxdoiorg//6/87 Research Article Approxiate Multidegree Reduction of λ-bézier Curves Gang Hu Huanxin Cao and Suxia Zhang Departent of

More information

3.8 Three Types of Convergence

3.8 Three Types of Convergence 3.8 Three Types of Convergence 3.8 Three Types of Convergence 93 Suppose that we are given a sequence functions {f k } k N on a set X and another function f on X. What does it ean for f k to converge to

More information

Some Perspective. Forces and Newton s Laws

Some Perspective. Forces and Newton s Laws Soe Perspective The language of Kineatics provides us with an efficient ethod for describing the otion of aterial objects, and we ll continue to ake refineents to it as we introduce additional types of

More information

Chapter 8 Deflection. Structural Mechanics 2 Dept of Architecture

Chapter 8 Deflection. Structural Mechanics 2 Dept of Architecture Chapter 8 Deflection Structural echanics Dept of rchitecture Outline Deflection diagras and the elastic curve Elastic-bea theory The double integration ethod oent-area theores Conjugate-bea ethod 8- Deflection

More information

The Weierstrass Approximation Theorem

The Weierstrass Approximation Theorem 36 The Weierstrass Approxiation Theore Recall that the fundaental idea underlying the construction of the real nubers is approxiation by the sipler rational nubers. Firstly, nubers are often deterined

More information

arxiv:physics/ v1 [physics.ed-ph] 19 Oct 2004

arxiv:physics/ v1 [physics.ed-ph] 19 Oct 2004 Orbits in a central force field: Bounded orbits Subhankar Ray Dept of Physics, Jadavpur University, Calcutta 7 3, India J. Shaanna Physics Departent, Visva Bharati University, Santiniketan 7335, India

More information

Cosine similarity and the Borda rule

Cosine similarity and the Borda rule Cosine siilarity and the Borda rule Yoko Kawada Abstract Cosine siilarity is a coonly used siilarity easure in coputer science. We propose a voting rule based on cosine siilarity, naely, the cosine siilarity

More information

CRASH COURSE IN PRECALCULUS

CRASH COURSE IN PRECALCULUS CRASH COURSE IN PRECALCULUS Shiah-Sen Wang The graphs are prepared by Chien-Lun Lai Based on : Precalculus: Mathematics for Calculus by J. Stuwart, L. Redin & S. Watson, 6th edition, 2012, Brooks/Cole

More information

1 Bounding the Margin

1 Bounding the Margin COS 511: Theoretical Machine Learning Lecturer: Rob Schapire Lecture #12 Scribe: Jian Min Si March 14, 2013 1 Bounding the Margin We are continuing the proof of a bound on the generalization error of AdaBoost

More information

The Hilbert Schmidt version of the commutator theorem for zero trace matrices

The Hilbert Schmidt version of the commutator theorem for zero trace matrices The Hilbert Schidt version of the coutator theore for zero trace atrices Oer Angel Gideon Schechtan March 205 Abstract Let A be a coplex atrix with zero trace. Then there are atrices B and C such that

More information

Support Vector Machine Classification of Uncertain and Imbalanced data using Robust Optimization

Support Vector Machine Classification of Uncertain and Imbalanced data using Robust Optimization Recent Researches in Coputer Science Support Vector Machine Classification of Uncertain and Ibalanced data using Robust Optiization RAGHAV PAT, THEODORE B. TRAFALIS, KASH BARKER School of Industrial Engineering

More information

PRÜFER SUBSTITUTIONS ON A COUPLED SYSTEM INVOLVING THE p-laplacian

PRÜFER SUBSTITUTIONS ON A COUPLED SYSTEM INVOLVING THE p-laplacian Electronic Journal of Differential Equations, Vol. 23 (23), No. 23, pp. 9. ISSN: 72-669. URL: http://ejde.ath.txstate.edu or http://ejde.ath.unt.edu ftp ejde.ath.txstate.edu PRÜFER SUBSTITUTIONS ON A COUPLED

More information

5.1 The derivative or the gradient of a curve. Definition and finding the gradient from first principles

5.1 The derivative or the gradient of a curve. Definition and finding the gradient from first principles Capter 5: Dierentiation In tis capter, we will study: 51 e derivative or te gradient o a curve Deinition and inding te gradient ro irst principles 5 Forulas or derivatives 5 e equation o te tangent line

More information

Foundations of Calculus. November 18, 2014

Foundations of Calculus. November 18, 2014 Foundations of Calculus November 18, 2014 Contents 1 Conic Sections 3 11 A review of the coordinate system 3 12 Conic Sections 4 121 Circle 4 122 Parabola 5 123 Ellipse 5 124 Hyperbola 6 2 Review of Functions

More information

Tutorial Exercises: Incorporating constraints

Tutorial Exercises: Incorporating constraints Tutorial Exercises: Incorporating constraints 1. A siple pendulu of length l ass is suspended fro a pivot of ass M that is free to slide on a frictionless wire frae in the shape of a parabola y = ax. The

More information

3.4 Conic sections. Such type of curves are called conics, because they arise from different slices through a cone

3.4 Conic sections. Such type of curves are called conics, because they arise from different slices through a cone 3.4 Conic sections Next we consider the objects resulting from ax 2 + bxy + cy 2 + + ey + f = 0. Such type of curves are called conics, because they arise from different slices through a cone Circles belong

More information

Geometry. figure (e.g. multilateral ABCDEF) into the figure A B C D E F is called homothety, or similarity transformation.

Geometry. figure (e.g. multilateral ABCDEF) into the figure A B C D E F is called homothety, or similarity transformation. ctober 15, 2017 Geoetry. Siilarity an hoothety. Theores an probles. efinition. Two figures are hoothetic with respect to a point, if for each point of one figure there is a corresponing point belonging

More information

Machine Learning Basics: Estimators, Bias and Variance

Machine Learning Basics: Estimators, Bias and Variance Machine Learning Basics: Estiators, Bias and Variance Sargur N. srihari@cedar.buffalo.edu This is part of lecture slides on Deep Learning: http://www.cedar.buffalo.edu/~srihari/cse676 1 Topics in Basics

More information

Geometry Beyond Algebra

Geometry Beyond Algebra r Q a 6 4R 5 + 4 Q R 4 4R Q 4R 4Q R 0 r + + + = R h Geoetry Beyond lgebra Hard Hard = Easy The Theore of Overlapped Polynoials (TOP) and its pplication to the Sawa Masayoshi s Sangaku Proble The dventure

More information

Solutions to the problems in Chapter 6 and 7

Solutions to the problems in Chapter 6 and 7 Solutions to the probles in Chapter 6 and 7 6.3 Pressure of a Feri gas at zero teperature The nuber of electrons N and the internal energy U, inthevoluev,are N = V D(ε)f(ε)dε, U = V εd(ε)f(ε)dε, () The

More information

KEMATH1 Calculus for Chemistry and Biochemistry Students. Francis Joseph H. Campeña, De La Salle University Manila

KEMATH1 Calculus for Chemistry and Biochemistry Students. Francis Joseph H. Campeña, De La Salle University Manila KEMATH1 Calculus for Chemistry and Biochemistry Students Francis Joseph H Campeña, De La Salle University Manila February 9, 2015 Contents 1 Conic Sections 2 11 A review of the coordinate system 2 12 Conic

More information

δ 12. We find a highly accurate analytic description of the functions δ 11 ( δ 0, n)

δ 12. We find a highly accurate analytic description of the functions δ 11 ( δ 0, n) Coplete-return spectru for a generalied Rosen-Zener two-state ter-crossing odel T.A. Shahverdyan, D.S. Mogilevtsev, V.M. Red kov, and A.M Ishkhanyan 3 Moscow Institute of Physics and Technology, 47 Dolgoprudni,

More information

MATH H53 : Mid-Term-1

MATH H53 : Mid-Term-1 MATH H53 : Mid-Term-1 22nd September, 215 Name: You have 8 minutes to answer the questions. Use of calculators or study materials including textbooks, notes etc. is not permitted. Answer the questions

More information

Time-Periodic Solutions of the Einstein s Field Equations

Time-Periodic Solutions of the Einstein s Field Equations Tie-Periodic Solutions of the Einstein s Field Equations De-Xing Kong 1 and Kefeng Liu 1 Departent of Matheatics Zhejiang University Hangzhou 31007 China Departent of Matheatics University of California

More information

13.2 Fully Polynomial Randomized Approximation Scheme for Permanent of Random 0-1 Matrices

13.2 Fully Polynomial Randomized Approximation Scheme for Permanent of Random 0-1 Matrices CS71 Randoness & Coputation Spring 018 Instructor: Alistair Sinclair Lecture 13: February 7 Disclaier: These notes have not been subjected to the usual scrutiny accorded to foral publications. They ay

More information

Uniform Approximation and Bernstein Polynomials with Coefficients in the Unit Interval

Uniform Approximation and Bernstein Polynomials with Coefficients in the Unit Interval Unifor Approxiation and Bernstein Polynoials with Coefficients in the Unit Interval Weiang Qian and Marc D. Riedel Electrical and Coputer Engineering, University of Minnesota 200 Union St. S.E. Minneapolis,

More information

Moment of Inertia. Terminology. Definitions Moment of inertia of a body with mass, m, about the x axis: Transfer Theorem - 1. ( )dm. = y 2 + z 2.

Moment of Inertia. Terminology. Definitions Moment of inertia of a body with mass, m, about the x axis: Transfer Theorem - 1. ( )dm. = y 2 + z 2. Terinology Moent of Inertia ME 202 Moent of inertia (MOI) = second ass oent Instead of ultiplying ass by distance to the first power (which gives the first ass oent), we ultiply it by distance to the second

More information

y mx 25m 25 4 circle. Then the perpendicular distance of tangent from the centre (0, 0) is the radius. Since tangent

y mx 25m 25 4 circle. Then the perpendicular distance of tangent from the centre (0, 0) is the radius. Since tangent Mathematics. The sides AB, BC and CA of ABC have, 4 and 5 interior points respectively on them as shown in the figure. The number of triangles that can be formed using these interior points is () 80 ()

More information

Lecture 17. Implicit differentiation. Making y the subject: If xy =1,y= x 1 & dy. changed to the subject of y. Note: Example 1.

Lecture 17. Implicit differentiation. Making y the subject: If xy =1,y= x 1 & dy. changed to the subject of y. Note: Example 1. Implicit differentiation. Lecture 17 Making y the subject: If xy 1,y x 1 & dy dx x 2. But xy y 2 1 is harder to be changed to the subject of y. Note: d dx (f(y)) f (y) dy dx Example 1. Find dy dx given

More information

Lower Bounds for Quantized Matrix Completion

Lower Bounds for Quantized Matrix Completion Lower Bounds for Quantized Matrix Copletion Mary Wootters and Yaniv Plan Departent of Matheatics University of Michigan Ann Arbor, MI Eail: wootters, yplan}@uich.edu Mark A. Davenport School of Elec. &

More information

Generalized eigenfunctions and a Borel Theorem on the Sierpinski Gasket.

Generalized eigenfunctions and a Borel Theorem on the Sierpinski Gasket. Generalized eigenfunctions and a Borel Theore on the Sierpinski Gasket. Kasso A. Okoudjou, Luke G. Rogers, and Robert S. Strichartz May 26, 2006 1 Introduction There is a well developed theory (see [5,

More information

Hyperbolic Horn Helical Mass Spectrometer (3HMS) James G. Hagerman Hagerman Technology LLC & Pacific Environmental Technologies April 2005

Hyperbolic Horn Helical Mass Spectrometer (3HMS) James G. Hagerman Hagerman Technology LLC & Pacific Environmental Technologies April 2005 Hyperbolic Horn Helical Mass Spectroeter (3HMS) Jaes G Hageran Hageran Technology LLC & Pacific Environental Technologies April 5 ABSTRACT This paper describes a new type of ass filter based on the REFIMS

More information

Celal S. Konor Release 1.1 (identical to 1.0) 3/21/08. 1-Hybrid isentropic-sigma vertical coordinate and governing equations in the free atmosphere

Celal S. Konor Release 1.1 (identical to 1.0) 3/21/08. 1-Hybrid isentropic-sigma vertical coordinate and governing equations in the free atmosphere Celal S. Konor Release. (identical to.0) 3/2/08 -Hybrid isentropic-siga vertical coordinate governing equations in the free atosphere This section describes the equations in the free atosphere of the odel.

More information

Conic section. Ans: c. Ans: a. Ans: c. Episode:43 Faculty: Prof. A. NAGARAJ. 1. A circle

Conic section. Ans: c. Ans: a. Ans: c. Episode:43 Faculty: Prof. A. NAGARAJ. 1. A circle Episode:43 Faculty: Prof. A. NAGARAJ Conic section 1. A circle gx fy c 0 is said to be imaginary circle if a) g + f = c b) g + f > c c) g + f < c d) g = f. If (1,-3) is the centre of the circle x y ax

More information

An EGZ generalization for 5 colors

An EGZ generalization for 5 colors An EGZ generalization for 5 colors David Grynkiewicz and Andrew Schultz July 6, 00 Abstract Let g zs(, k) (g zs(, k + 1)) be the inial integer such that any coloring of the integers fro U U k 1,..., g

More information

Chaotic Coupled Map Lattices

Chaotic Coupled Map Lattices Chaotic Coupled Map Lattices Author: Dustin Keys Advisors: Dr. Robert Indik, Dr. Kevin Lin 1 Introduction When a syste of chaotic aps is coupled in a way that allows the to share inforation about each

More information

Linear recurrences and asymptotic behavior of exponential sums of symmetric boolean functions

Linear recurrences and asymptotic behavior of exponential sums of symmetric boolean functions Linear recurrences and asyptotic behavior of exponential sus of syetric boolean functions Francis N. Castro Departent of Matheatics University of Puerto Rico, San Juan, PR 00931 francis.castro@upr.edu

More information

TWO THEOREMS ON THE FOCUS-SHARING ELLIPSES: A THREE-DIMENSIONAL VIEW

TWO THEOREMS ON THE FOCUS-SHARING ELLIPSES: A THREE-DIMENSIONAL VIEW TWO THEOREMS ON THE FOCUS-SHARING ELLIPSES: A THREE-DIMENSIONAL VIEW ILYA I. BOGDANOV Abstract. Consider three ellipses each two of which share a common focus. The radical axes of the pairs of these ellipses

More information

TRAVELING WAVE SOLUTIONS OF THE POROUS MEDIUM EQUATION. Laxmi P. Paudel. Dissertation Prepared for the Degree of DOCTOR OF PHILOSOPHY

TRAVELING WAVE SOLUTIONS OF THE POROUS MEDIUM EQUATION. Laxmi P. Paudel. Dissertation Prepared for the Degree of DOCTOR OF PHILOSOPHY TRAVELING WAVE SOLUTIONS OF THE POROUS MEDIUM EQUATION Laxi P Paudel Dissertation Prepared for the Degree of DOCTOR OF PHILOSOPHY UNIVERSITY OF NORTH TEXAS May 013 APPROVED: Joseph Iaia, Major Professor

More information

Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers Roy D. Yates and David J.

Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers Roy D. Yates and David J. Probability and Stochastic Processes: A Friendly Introduction for Electrical and oputer Engineers Roy D. Yates and David J. Goodan Proble Solutions : Yates and Goodan,1..3 1.3.1 1.4.6 1.4.7 1.4.8 1..6

More information

A Bernstein-Markov Theorem for Normed Spaces

A Bernstein-Markov Theorem for Normed Spaces A Bernstein-Markov Theore for Nored Spaces Lawrence A. Harris Departent of Matheatics, University of Kentucky Lexington, Kentucky 40506-0027 Abstract Let X and Y be real nored linear spaces and let φ :

More information

Lecture 21. Interior Point Methods Setup and Algorithm

Lecture 21. Interior Point Methods Setup and Algorithm Lecture 21 Interior Point Methods In 1984, Kararkar introduced a new weakly polynoial tie algorith for solving LPs [Kar84a], [Kar84b]. His algorith was theoretically faster than the ellipsoid ethod and

More information

Solving Pell Equations

Solving Pell Equations Solving Pell Equations Matthew Wright May 2, 2006 Departent of Matheatical Sciences Messiah College Grantha, PA Dr. Laarr Wider, advisor This paper is subitted in partial fulfillent of the requireents

More information

ADVANCES ON THE BESSIS- MOUSSA-VILLANI TRACE CONJECTURE

ADVANCES ON THE BESSIS- MOUSSA-VILLANI TRACE CONJECTURE ADVANCES ON THE BESSIS- MOUSSA-VILLANI TRACE CONJECTURE CHRISTOPHER J. HILLAR Abstract. A long-standing conjecture asserts that the polynoial p(t = Tr(A + tb ] has nonnegative coefficients whenever is

More information

are in c) A B (D) 2 = {4,5,6} by = {(4,4), (5,5), (6,6)} is (C) (B) 0 < (C) 0 = 8, = 5 = 8, = 8 (B) (D) (C) 2 +

are in c) A B (D) 2 = {4,5,6} by = {(4,4), (5,5), (6,6)} is (C) (B) 0 < (C) 0 = 8, = 5 = 8, = 8 (B) (D) (C) 2 + 1. If are in GP then AP GP are in HP 2. The sum to infinity of the series 1 3. The set B-A a subset of a) A c) A B b) B d)null set 4. The converse of the statement if 3 3 6 then I am the president of USA

More information

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and This article appeared in a ournal published by Elsevier. The attached copy is furnished to the author for internal non-coercial research and education use, including for instruction at the authors institution

More information

TARGET : JEE 2013 SCORE. JEE (Advanced) Home Assignment # 03. Kota Chandigarh Ahmedabad

TARGET : JEE 2013 SCORE. JEE (Advanced) Home Assignment # 03. Kota Chandigarh Ahmedabad TARGT : J 01 SCOR J (Advanced) Home Assignment # 0 Kota Chandigarh Ahmedabad J-Mathematics HOM ASSIGNMNT # 0 STRAIGHT OBJCTIV TYP 1. If x + y = 0 is a tangent at the vertex of a parabola and x + y 7 =

More information

TEST OF HOMOGENEITY OF PARALLEL SAMPLES FROM LOGNORMAL POPULATIONS WITH UNEQUAL VARIANCES

TEST OF HOMOGENEITY OF PARALLEL SAMPLES FROM LOGNORMAL POPULATIONS WITH UNEQUAL VARIANCES TEST OF HOMOGENEITY OF PARALLEL SAMPLES FROM LOGNORMAL POPULATIONS WITH UNEQUAL VARIANCES S. E. Ahed, R. J. Tokins and A. I. Volodin Departent of Matheatics and Statistics University of Regina Regina,

More information

The degree of a typical vertex in generalized random intersection graph models

The degree of a typical vertex in generalized random intersection graph models Discrete Matheatics 306 006 15 165 www.elsevier.co/locate/disc The degree of a typical vertex in generalized rando intersection graph odels Jerzy Jaworski a, Michał Karoński a, Dudley Stark b a Departent

More information

CIRCLES: #1. What is an equation of the circle at the origin and radius 12?

CIRCLES: #1. What is an equation of the circle at the origin and radius 12? 1 Pre-AP Algebra II Chapter 10 Test Review Standards/Goals: E.3.a.: I can identify conic sections (parabola, circle, ellipse, hyperbola) from their equations in standard form. E.3.b.: I can graph circles

More information

Senior Math Circles February 18, 2009 Conics III

Senior Math Circles February 18, 2009 Conics III University of Waterloo Faculty of Mathematics Senior Math Circles February 18, 2009 Conics III Centre for Education in Mathematics and Computing Eccentricity of Conics Fix a point F called the focus, a

More information

Introduction to Computer Graphics (Lecture No 07) Ellipse and Other Curves

Introduction to Computer Graphics (Lecture No 07) Ellipse and Other Curves Introduction to Computer Graphics (Lecture No 07) Ellipse and Other Curves 7.1 Ellipse An ellipse is a curve that is the locus of all points in the plane the sum of whose distances r1 and r from two fixed

More information

13 Harmonic oscillator revisited: Dirac s approach and introduction to Second Quantization

13 Harmonic oscillator revisited: Dirac s approach and introduction to Second Quantization 3 Haronic oscillator revisited: Dirac s approach and introduction to Second Quantization. Dirac cae up with a ore elegant way to solve the haronic oscillator proble. We will now study this approach. The

More information

MODULAR HYPERBOLAS AND THE CONGRUENCE ax 1 x 2 x k + bx k+1 x k+2 x 2k c (mod m)

MODULAR HYPERBOLAS AND THE CONGRUENCE ax 1 x 2 x k + bx k+1 x k+2 x 2k c (mod m) #A37 INTEGERS 8 (208) MODULAR HYPERBOLAS AND THE CONGRUENCE ax x 2 x k + bx k+ x k+2 x 2k c (od ) Anwar Ayyad Departent of Matheatics, Al Azhar University, Gaza Strip, Palestine anwarayyad@yahoo.co Todd

More information