## Tag Archives: Tristan Needham

### What does (∂h/∂x)dx + (∂h/∂y)dy + (∂h/∂z)dz really mean?

We’ve all seen (∂h/∂x)dx + (∂h/∂y)dy + (∂h/∂z)dz many times and have used it to calculate without understanding what the various symbols  actually mean.  In my case, it’s just another example of mouthing mathematical incantations without understanding them, something I became very good at at young age — see https://luysii.wordpress.com/2022/06/27/the-chinese-room-argument-understanding-math-and-the-imposter-syndrome/ for the gory details.

And now, finally, within a month of my 85th birthday, I finally understand what’s going on by reading only the first 25 pages of “Elementary Differential Geometry” revised second edition 2006 by Barrett O’Neill.

I was pointed to it by the marvelous Visual Differential Geometry by Tristan Needham, about which I’ve written 3 posts — this link has references to the other two — https://luysii.wordpress.com/2022/03/07/visual-differential-geometry-and-forms-q-take-3/

He describes O’Neill’s book as follows.  “First published in 1966, this trail-blazing text pioneered the use of Forms at the undergraduate level.  Today more than a half-century later, O’Neill’s work remains, in my view the single most clear-eyed, elegant and (ironically) modern treatment of the subject available — present company excepted! — at the undergraduate level”

It took a lot of work to untangle the notation (typical of all works in Differential Geometry). There is an old joke “differential geometry is the study of properties that are invariant under change of notation” which is funny because it is so close to the truth (John M. Lee)

So armed with no more than calculus 101, knowing what a vector space is,  and a good deal of notational patience, the meaning of (∂h/∂x)dx + (∂h/∂y)dy + (∂h/∂z)dz (including what dx, dy and dz really are) should be within your grasp.

We begin with R^3, the set of triples of real numbers (a_1, a_2, a_3) where _ means that 1, 2, 3 are taken as subscripts). Interestingly, these aren’t vectors to O’Neill which will be defined shortly.  All 3 components of a triple can be multiplied by a real number c — giving (c*a_1, c*a_2, c*a_3). Pairs of triples can be added.  This makes R^3 into a vector space (which O’Neill calls Euclidean 3-space), the components of which are triples (which O’Neill calls points), but that is not how O’Neill defines a vector, which are pairs of points p = (p_1, p_2, p_3) and v = (v_1, v_2, v_3) — we’ll see why shortly.

A tangent vector to point p in R^3 is called a tangent vector to p (and is written v_p) and is defined as an ordered pair of points (p, v) where

p is the point of application of v_p (aka the tail of p)

v is the vector part of v_p (aka the tip of v_p)

It is visualized as an arrow whose tail is at p and whose tip (barb) is at  p + v (remember you are allowed to add points).  In the visualization of v_p, v does not appear.

The tangent space of R^3 at p is written T_pR^3 and is the set of vectors (p, v) such that p is constant and v varies over all possible points.

Each p in R^3 has its own tangent space, and tangent vectors in different tangent spaces can’t be added.

Next up functions.

A real value function on R^3 is written

f :  R^3 –> R^1 (the real numbers)

f : (a_1, a_2, a_3) |—> c (some real number)

This is typical of the way functions are written in more advanced math, with the first line giving the domain (R^3) of the function and the range of the function (R^1) and the second line giving what happens to a typical element of the domain on application of the function to it.

O’Neill assumes that all the functions on domain R^3 have continuous derivatives of all orders.  So the functions are smooth, differentiable or C^infinity — take your pick — they are equivalent.

The assumption of differentiability means that you have some mechanism for seeing how close two points are to each other.  He doesn’t say it until later, but this assumes the usual distance metric using the Pythagorean theorem — if you’ve taken calc. 101 you know what these are.

For mental visualization it’s better to think of the function as from R^2 (x and y variables — e.g,. the Euclidean plane) to the real numbers.  This is the classic topographic map, which tells how high over the ground you are at each point.

Now at last we’re getting close to (∂f/∂x)dx + (∂f/∂y)dy + (∂f/∂z)dz.

So now you’re on a ridge ascending to the summit of your favorite mountain.  The height function tells you how high your are where you’re standing (call this point p), but what you really want to know is which way to go to get to the peak.  You want to find a direction in which height is increasing.   Enter the directional derivative (of the height function)  Clearly height drops off on either side of the ridge and increases or decreases along the ridge.   Equally clearly there is no single directional derivative here (as there would be for a function g : R^1 –> R^1).  The directional derivative  depends on p (where you are) and v the direction you choose — this is why O’Neill defines tangent vectors by two points (p, and v)

So the directional derivative requires two functions

the height function h : R^3 –> R^1

the direction function f : p + t*v where t is in R^1.  This gives the a line through p going in direction v

So the directional derivative of  h at p is

d/dt  (h (p + t*v)) | _t = 0  ; take the limit of h (p + t*v)  as t approaches zero

Causing me a lot of confusion, O’Neill gives the directional derivative the following name v_p[h] — which gives you no sense that a derivative of anything is involved.  This is his equation

v_p[f] = d/dt  (h (p + t*v)) | _t = 0

Notice that changing p (say to the peak of the mountain) changes the directional derivative —  all of them point down.   This is why O’Neill defines tangent vectors using two points (p, v).

Now a few more functions and the chain rule and we’re about done.

x :    R^3                    –>  R^1

x : (v_1, v_2, v_3 ) |–>  v_1

similarly y :R^3 –> R^1 picks out the y coordinate of (v_1, v_2, v_3 )  e.g. v_2

Let’s look at p + t*v in coordinate form, remembering what p and v are that way

p + t*v  = ( p_1 + t * v_1, p_2 + t * v_2, p_3 + t * v_3)

Remember that we defined f = p  + t *v

so df/dt = d( p + t*v )/dt

expanding

df’/dt= d( p_1 + t * v_1, p_2 + t * v_2, p_3 + t * v_3)/dt = (v_1, v_2, v_3)

Let’s be definite about what h : R^3 –> R^1 actually is

h : (x, y, z) |—> x^2 * y^3 *z ^4 meaning you must use partial derivatives

so ∂h/∂x = 2 x * y^3 * z* 4,  etc.,

Look at v_p[h] = d/dt  (h (p + t*v)) | _t = 0 again

It’s really v_p[h] = d/dt (h (f (t))|_=0

so it’s time for the chain rule

d/dt (h (f (t)) = (dh/df ) * (df/dt)

dh/df in coordinates is really

(∂h/∂x, ∂h/∂y,∂h/∂z)

df/dt in coordinates is really

(v_1, v_2, v_3)

But the chain rule is applied to each of the three terms

so what you have is d/dt (h (f (t))  = (∂h/∂x * v_1,  ∂h/∂y * v_2, ∂h/∂z * v_3)

I left one thing out.  The |_=0

So to do this you need to plug in the numbers (evaluating everything at p) and sum so what you get is

v_p[h] = ∂h/∂x * v_1 +  ∂h/∂y * v_2 +  ∂h/∂z * v_3

We need one more definition. Recall that the tangent space of R^3 at p is written T_pR^3 and is the set of vectors (p, v) such that p is constant and v varies over all possible points.

The set of all tangent spaces over R^3 is written (TR^3)

Finally on p. 24 O’Neill defines what you’ve all been waiting for :  dh

dh : TR^3 –> R^1

dh : p  ——>  v_p[h] = ∂h/∂x * v_1 +  ∂h/∂y * v_2 +  ∂h/∂z * v_3

One last bit of manipulation — what is dx (and dy and dz)?

we know that  the function x is defined as follows

x :    R^3                    –>  R^1

x : (v_1, v_2, v_3 ) |–>  v_1

so dx = (dx/dx, dx/dy, dx/dz)|_=0

is just  v_1

so at (very) long last we have

dh : TR^3 –> R^1

dh : p  ——>  v_p[h] = ∂h/∂x * dx +  ∂h/∂y * dy +  ∂h/∂z * dz

Remember ∂h/∂x, ∂h/∂y,  ∂h/∂z are all evaluated at p = (p_1, p_2, p_3)

So it’s a (fairly) simple matter to apply dh to any point p in R^3 and any direction  (v_1, v_2, v_3) in R^3 to get the directional derivative

Amen. Selah.

### What is dx really?

“Differential geometry is the study of properties that are invariant under change of notion”  — Preface p. vii of “Introduction to Smooth Manifolds” J. M. Lee second edition.  Lee says this is “funny primarily because it is so close to the truth”.

Having ascended to a substantial base camp for the assault on the Einstein Field equations (e.g. understanding the Riemann curvature tensor), I thought I’d take a break and follow Needham’s advice about another math book “Elementary Differential Geometry” 2nd edition (revised 2006) by Barrett O’Neill.  “First published in 1966, this trail-blazing text pioneered the use of Forms at the undergraduate level.  Today, more than a half-century later, O’Neill’s work remains, in my view, the single most clear-eyed, elegant and (ironically) modern treatment of the subject available — present company excepted! — at the undergraduate level.”

Anyone taking calculus has seen plenty of dx’s — in derivatives, in integrals etc. etc..  They’re rarely explained.  O’Neill will get you there in just the first 24 pages.  One more page and you’ll understand

df =  (partial f/partial x) * dx + (partial f/partial y) * dy + (partial f/partial z) * dz

which you’ve doubtless seen before primarily as (heiroglyphics) before you moved on.

Is it easy?  No, not unless you read definitions and internalize them immediately.  The definitions are very clearly explained.

His definition of vector is a bit different — two points in Euclidean 3-space (written R^3 which is the only space he talks about in the first 25 pages).  His 3-space is actually a vector space in which point can be added and scalar multiplied.

You’ll need to bone up on the chain rule from calculus 101.

A few more definitions — natural coordinate functions, tangent space to R^3 at p, vector field on R^3, pointwise principle, natural frame field, Euclidean coordinate function (written x_i, where i is in { 1, 2, 3 } ), derivative of a function in direction of vector v (e.g. directional derivative), operation of a vector on a function, tangent vector, 1-form, dual space. I had to write them down to keep them straight as they’re mixed in paragraphs containing explanatory text.

and

at long last,

differential of x_i (written dx_i)

All is not perfect.  On p. 28 you are introduced to the alternation rule

dx_i ^ dx_j = – dx_j ^ dx_i with no justification whatsoever

On p. 30 you are given the formula for the exterior derivative of a one form again with no justification.  So its back to mumbling incantations and plug and chug

### Understanding the Riemann curvature tensor is like doing a spinal tap

Back in the day when I was doing spinal taps, I spent far more time setting them up (positioning the patient so that the long axis of the spinal column was parallel to the floor and the vertical axis of the recumbent patient was perpendicular to the floor) than actually doing the tap.  Why? because then, all I had to do was have the needle parallel to the floor, with no guessing about how to angle it when the patient had rolled (usually forward into the less than firm mattress of the hospital bed).

So it is with finally seeing what the Riemann curvature tensor actually is, why it is the way it is, and why the notation describing it is such a mess.  Finally on p. 290 of Needham’s marvelous book “Visual Differential Geometry and Forms” the Riemann curvature tensor is revealed in all its glory.  Understanding it takes far less time than understanding the mathematical (and geometric) scaffolding required to describe it, a la spinal taps.

Over the years while studying relativity, I’ve seen it in one form or other (always algebraic) without understanding what the algebra was really describing.

Needham will get you there, but you have to understand a lot of other things first. Fortunately almost all of them are described visually, so you see what the algebra is trying to describe.  Along the way you will see what the Lie bracket of two vector fields is all about along with holonomy.  And you will really understand what curvature is.  And Needham will give you 3 ways to understand parallel transport (which underlies everything — thanks Ashutosh)

Needham starts off with Gauss’s definition of curvature of a surface — the angular excess of a triangle, divided by its area.

Here is why this definition is enough to show you why the surface of a sphere is curved.   Go to the equator.  Mark point one, then point two 1/4 of the way around the sphere.  Form longitudes (perpendiculars) there and extend them as great circles toward the North pole. You now have a triangle containing 3 right angles, (clearly an angular excess from Euclid who states that the sum the angles of a triangle is two right angles).  The reason, of course, is because the sphere is curved.

Ever since I met a classmate 12 years ago at a college reunion who was a relativist working with Hawking, I decided to try to learn relativity so I’d have something intelligent to say to him if we ever met again (COVID19 stopped all that although we’re still both alive).

Now that I understand what the math of relativity is trying to describe, I may be able to understand general relativity.

Be prepared for a lot of work, but do start with Needham’s book.  Here are some links to other things I’ve written about it.  It will take some getting used to as it is very different from any math book you’ve ever read (except Needham’s other book).

### A visual proof of the the theorem egregium of Gauss

Nothing better illustrates the difference between the intuitive understanding that something is true and being convinced by logic that something is true  than the visual proof of the theorem egregium of Gauss found in “Visual Differential Geometry and Forms” by Tristan Needham and  the 9 step algebraic proof in  “The Geometry of Spacetime” by Jim Callahan.

Mathematicians attempt to tie down the Gulliver of our powerful appreciation of space with Lilliputian strands of logic.

First: some background on the neurology of vision and our perception of space and why it is so compelling to us.

In the old days, we neurologists figured out what the brain was doing by studying what was lost when parts of the brain were destroyed (usually by strokes, but sometimes by tumors or trauma).  This wasn’t terribly logical, as pulling the plug on a lamp plunges you in darkness, but the plug has nothing to do with how the lightbulb or LED produces light.  Even so,  it was clear that the occipital lobe was important — destroy it on both sides and you are blind — https://en.wikipedia.org/wiki/Occipital_lobe but the occipital lobe accounts for only 10% of the gray matter of the cerebral cortex.

The information flowing into your brain from your eyes is enormous.  The optic nerve connecting the eyeball to the brain has a million fibers, and they can fire ‘up to 500 times a second.  If each firing (nerve impulse) is a bit, then that’s an information flow into your brain of a gigaBit/second.   This information is highly processed by the neurons and receptors in the 10 layers of the retina. Over 30 retinal cell types in our retinas are known, each responding to a different aspect of the visual stimulus.  For instance, there are cells responding to color, to movement in one direction, to a light stimulus turning on, to a light stimulus turning off, etc. etc.

So how does the relatively small occipital lobe deal with this? It doesn’t.  At least half of your the brain responds to visual stimuli.  How do we know?   It’s complicated, but something called functional Magnetic Resonance Imaging (fMRI) is able to show us increased neuronal activity primarily by the increase in blood flow it causes.

Given that half of your brain is processing what you see, it makes sense to use it to ‘see’ what’s going on in Mathematics involving space.  This is where Tristan Needham’s books come in.

I’ve written several posts about them.

and Here — https://luysii.wordpress.com/2022/03/07/visual-differential-geometry-and-forms-q-take-3/

OK, so what is the theorem egregium?  Look at any object (say a banana). You can see how curved it is by just looking at its surface (e.g. how it looks in the 3 dimensional space of our existence).  Gauss showed that you don’t
have to even look at an object in 3 space,  just perform local measurements (using the distance between surface points, e.g. the metric e.g.  the metric tensor) .  Curvature is intrinsic to the surface itself, and you don’t have to get outside of the surface (as we are) to find it.

The idea (and mathematical machinery) has been extended to the 3 dimensional space we live in (something we can’t get outside of).  Is our  universe curved or not? To study the question is to determine its intrinsic curvature by extrapolating the tools Gauss gave us to higher dimensions and comparing the mathematical results with experimental observation. The elephant in the room is general relativity which would be impossible without this (which is why I’m studying the theorem egregium in the first place).

So how does Callahan phrase and prove the theorem egregium? He defines curvature as the ratio of the area on a (small) patch on the surface to the area of another patch on the unit sphere. If you took some vector calculus, you’ll know that the area spanned by two nonCollinear vectors is the numeric value of their cross product.

The vectors Callahan needs for the cross product are the normal vectors to the surface.  Herein beginneth the algebra. Callahan parameterizes the surface in 3 space from a region in the plane, uses the metric of the surface to determine a formula for the normal vector to the surface  at a point (which has 3 components  x , y and z,  each of which is the sum of 4 elements, each of which is the product of a second order derivative with a first order derivative of the metric). Forming the cross product of the normal vectors and writing it out is an algebraic nightmare.  At this point you know you are describing something called curvature, but you have no clear conception of what curvature is.  But you have a clear definition in terms of the ratio of areas, which soon disappears in a massive (but necessary) algebraic fandango.

On pages 258 – 262 Callahan breaks down the proof into 9 steps involving various mathematical functions of the metric and its derivatives such as  Christoffel symbols,  the Riemann curvature tensors etc. etc.  It is logically complete, logically convincing, and shows that all this mathematical machinery arises from the metric (intrinsic to the surface) and its derivatives (some as high as third order).

For this we all owe Callahan a great debt.  But unfortunately, although I believe it,  I don’t see it.  This certainly isn’t to denigrate Callahan, who has helped me through his book, and a guy who I consider a friend as I’ve drunk beer with him and his wife while  listening to Irish music in a dive bar north of Amherst.

Callahan’s proof is the way Gauss himself did it and Callahan told me that Gauss didn’t have the notational tools we have today making the theorem even more outstanding (egregious).

Well now,  onto Needham’s geometrical proof.  Disabuse yourself of the notion that it won’t involve much intellectual work on your part even though it uses the geometric intuition you were born with (the green glasses of Immanuel Kant — http://onemillionpoints.blogspot.com/2009/07/kant-for-dummies-green-sunglasses.html)

Needham’s definition of curvature uses angular excess of a triangle.  Angles are measured in radians, which is the ratio of the arc subtended by the angle to the radius of the circle (not the circumference as I thought I remembered).  Since the circumference of a circle is 2*pi*radius, radian measure varies from 0 to 2*pi.   So a right angle is pi/2 radians.

Here is a triangle with angular excess.  Start with a sphere of radius R.  Go to the north pol and drop a longitude down to the equator.  It meets the equator at a right angle (pi/2).  Go back to the north pole, form an angle of pi/2 with the first longitude, and drop another longitude at that angle which meets the equator at an angle of pi/2.   The two points on the equator and the north pole form a triangle, with total internal angles of 3*(pi/2).  In plane geometry we know that the total angles of a triangle is 2 (pi/2).  (Interestingly this depends on the parallel postulate. See if you can figure out why).  So the angular excess of our triangle is pi/2.  Nothing complicated to understand (or visualize) here.

Needham defines the curvature of the triangle (and any closed area) as the ratio between the angular excess of the triangle to its area

What is the area of the triangle?  Well, the volume of a sphere is (4/3) pi * r^3, and its area is the integral (4 pi * r^2).  The area of the north hemisphere, is 2 pi *r^2, and the area of the triangle just made is 1/2 * Pi * r^2.

So the curvature of the triangle is (pi/2) / (1/2 * pi * r^2) = 1 / r^2.   More to the point, this is the curvature of a sphere of radius r.

At this point you should have a geometric intuition of just what curvature is, and how to find it.  So when you are embroiled in the algebra in higher dimensions trying to describe curvature there, you will have a mental image of what the algebra is attempting to describe, rather than just the symbols and machinations of the algebra itself (the Lilliputian strands of logic tying down the Gulliver of curvature).

The road from here to the Einstein gravitational field equations (p. 326 of Needham) and one I haven’t so far traversed,  presently is about 50 pages.Just to get to this point however,  you have been exposed to comprehensible geometrical expositions, of geodesics, holonomy,  parallel transport and vector fields, and you should have mental images of them all.Interested?  Be prepared to work, and to reorient how you think about these things if you’ve met them before.  The 3 links mentioned about will give you a glimpse of Needham’s style.  You probably should read them next.

# The Chinese Room Argument

was first published in a 1980 article by American philosopher John Searle. He imagines himself alone in a room following a computer program for responding to Chinese characters slipped under the door. Searle understands nothing of Chinese, and yet, by following the program for manipulating symbols and numerals just as a computer does, he sends appropriate strings of Chinese characters back out under the door, and this leads those outside to mistakenly suppose there is a Chinese speaker in the room.

So it was with me and math as an undergraduate due to a history dating back to age 10.  I hit college being very good at manipulating symbols whose meaning I was never given to understand.  I grew up 45 miles from the nearest synagogue.  My fanatically religious grandfather thought it was better not to attend services at all than to drive up there on the Sabbath.  My father was a young lawyer building a practice, and couldn’t close his office on Friday.   So my he taught me how to read Hebrew letters and reproduce how they sound, so I could read from the Torah at my Bar Mitzvah (which I did comprehending nothing).  Since I’m musical, learning the cantillations under the letters wasn’t a problem.

I’ve always loved math and solving problems of the plug and chug variety was no problem.  I’d become adept years earlier at this type of thing thanks to my religiously rigid grandfather.   It was the imposter syndrome writ large.  I’ve never felt like this about organic chemistry and it made a good deal of intuitive sense the first time I ran into it.  For why have a look at — https://luysii.wordpress.com/2012/09/11/why-math-is-hard-for-me-and-organic-chemistry-is-easy/

If there is anything in math full of arcane symbols calling for lots of mechanical manipulation, it is the differential geometry and tensors needed to understand General relativity.   So I’ve plowed through a lot of it, but still don’t see what’s really going on.

Enter Tristan Needham’s book “Visual Differential Geometry and Forms”.  I’ve written about it several times
and Here — https://luysii.wordpress.com/2022/03/07/visual-differential-geometry-and-forms-q-take-3/

If you’ve studied any math, his approach will take getting used to as it’s purely visual and very UNalgebraic.  But what is curvature but a geometric concept.

So at present I’m about 80 pages away from completing Needham’s discussion of general relativity.  I now have an intuitive understanding of curvature, torsion, holonomy, geodesics and the Gauss map that I never had before.   It is very slow going, but very clear.  Hopefully I’ll make it to p. 333.  Wish me luck.

### Visual Differential Geometry and Forms — Take 3

Visual Differential Geometry and Forms is a terrific math book about which I’ve written

and

but first some neurology.

In the old days we neurologists figured out what the brain was doing by studying what was lost when parts of the brain were destroyed (usually by strokes, but sometimes by tumors or trauma).  Not terribly logical, as pulling the plug on a lamp plunges you in darkness, but the plug has nothing to do with how the lightbulb or LED produces light.  It was clear that the occipital lobe was important — destroy it on both sides and you are blind — https://en.wikipedia.org/wiki/Occipital_lobe but it’s only 10% of the gray matter of the cerebral cortex.

The information flowing into your brain from your eyes is enormous.  The optic nerve connecting the eyeball to the brain has a million fibers, and they can fire ‘up to 500 times a second.  If each firing (nerve impulse) is a bit, then that’s an information flow into your brain of a gigaBit/second.   This information is highly processed by the neurons and receptors in the 10 layers of the retina.  There are many different cell types — cells responding to color, to movement in one direction, to a light stimulus turning on, to a light stimulus turning off, etc. etc.   Over 30 cell types have been described, each responding to a different aspect of the visual stimulus.

So how does the relatively small occipital lobe deal with this? It doesn’t.At least half of your the brain responds to visual stimuli.  How do we know?   It’s complicated, but something called functional Magnetic Resonance Imaging (fMRI) picks up increased neuronal activity (primarily by the increase in blood flow it causes).

Given that half your brain is processing what you see, it makes sense to use it to ‘see’ what’s going on in Mathematics.  This is where Tristan Needham’s books come in.

If you’ve studied math at the college level with some calculus you shouldn’t have much trouble.  But you definitely need to look at Euclid as it’s used heavily throughout. Much use is made of similar triangles to derive relationships.

I’ll assume you’ve read the first two posts mentioned above.  Needham’s description of curvature and torsion of curves in 3 dimensional space is terrific.  They play a huge role in relativity, and I was able to mouth the formulas for them but they remained incomprehensible to me, as they are just symbols on the page.  Hopefully the discussion further on in the book will let me ‘see’ what they are when it comes to tensors.

He does skip about a bit passing Euclid when he tell how people living t on a 2 dimensional surface could tell it wasn’t flat (p. 19).  It involves numerically measuring the circumference of a circle.  But this involves a metric and putting numbers on lines, something Euclid never did.

Things really get interesting when he started talking about how Newton found the center of curvature of an arbitrary curve.  Typically Needham doesn’t really define curve, something obvious to a geometer, but it’s clear the curve is continuous.  Later he lets it slip that the curve is differentiable (without saying so).

So what did Newton do?   Start with a point p and find its normal line.  Then find point q near p on the curve and find its normal line and see where they intersect.  The center of curvature at p is the point of intersection of the normals as the points get closer and closer to p.

This made wonder how Newton could find the normal to an arbitrary continuous curve.  It would be easy if he knew the tangents, because Euclid very early on (Proposition 11 Book 1) tells you how to construct the perpendicular to a straight line.  It is easy for Euclid to find the tangent to a circle at point p — it’s just the perpendicular to the line formed between the center of the circle (where you put one point of the compass used by Newton) and the circle itself (the other point of the compass.

But how does Newton find the tangent to an arbitrary continuous curve?  I couldn’t find any place that he did it, but calc. 101 says that you just find the limit of secants ending at p as the other point gets closer and closer.  Clearly this is a derivative of sorts.

Finally Needham tells you that his curves in 3 dimensions are differentiable in the following oblique way.  On p. 106 he says that “each infinitesimal segment (of a curve) nevertheless lies in a plane.”  This tells you that the curve has a tangent, and a normal to it at 90 degrees (but not necessarily in the plane).  So it must be differentiable (oblique no?).   On p. 107 he differentiates the tangent in the infinitesimal plane to get the principal normal (which DOES  lie in the plane).  Shades of Bishop Berkeley (form Berkeley California is named) — differentiating the ghost of a departed object.

Addendum: 28 March ’22:  It’s was impossible for me to find a definition of surface even reading the first 164 pages.  Needham highly recommends a book I own “Elementary Differential Geometry (revised 2nd edition) by Barrett O’Neill calling it “the single most clear-eyed elegant, and (ironically) modern treatment of the subject  . . .  at the undergraduate level”.  The first edition was 1966.   In the preface to his book O’Neill says “One weakness of classical differential geometry is its lack of any adequate definition of surface”.    No wonder I had trouble.

So it’s great fun going through the book, get to “Einstein’s Curved Spacetime” Chapter 30 p. 307, “The Einstein FIeld Equation (with Matter) in Geometrical Form” complete with picture p. 326.

More Later.

### A premature book review and a 60 year history with complex variables in 4 acts

“Visual Differential Geometry and Forms” (VDGF) by Tristan Needham is an incredible book.  Here is a premature review having only been through the first 82 pages of 464 pages of text.

Here’s why.

While mathematicians may try to tie down the visual Gulliver with Lilliputian strands of logic, there is always far more information in visual stimuli than logic can appreciate.  There is no such a thing as a pure visual percept (a la Bertrand Russell), as visual processing begins within the 10 layers of the retina and continues on from there.  Remember: half your brain is involved in processing visual information.  Which is a long winded way of saying that Needham’s visual approach to curvature and other visual constructs is an excellent idea.
Needham loves complex variables and geometry and his book is full of pictures (probably on 50% of the pages).

My history with complex variables goes back over 60 years and occurs in 4 acts.

Act I:  Complex variable course as an undergraduate. Time late 50s.  Instructor Raymond Smullyan a man who, while in this world, was definitely not of it.  He really wasn’t a bad instructor but he appeared to be thinking about something else most of the time.

Act II: Complex variable course at Rocky Mountain College, Billings Montana.  Time early 80s.  The instructor and MIT PhD was excellent.  Unfortunately I can’t remember his name.  I took complex variables again, because I’d been knocked out for probably 30 minutes the previous year and wanted to see if I could still think about the hard stuff.

Act III: 1999 The publication of Needham’s first book — Visual Complex Analysis.  Absolutely unique at the time, full of pictures with a glowing recommendation from Roger Penrose, Needham’s PhD advisor.  I read parts of it, but really didn’t appreciate it.

Act IV 2021 the publication of Needham’s second book, and the subject of this partial review.  Just what I wanted after studying differential geometry with a view to really understanding general relativity, so I could read a classmate’s book on the subject.  Just like VCA, and I got through 82 pages or so, before I realized I should go back and go through the relevant parts (several hundred pages) of VCA again, which is where I am now.  Euclid is all you need for the geometry of VCA, but any extra math you know won’t hurt.

I can’t recommend both strongly enough, particularly if you’ve been studying differential geometry and physics.  There really is a reason for saying “I see it” when you understand something.

Both books are engagingly and informally written, and I can’t recommend them enough (well at least the first 82 pages of VDGF).