Lasers
Optics
Physics

Three Ingredients

As I write this, I’m sitting in the offices of Hashrocket in Jacksonville, Fl, looking at the ocean and balancing a cappuccino on my laptop. It actually makes it difficult to type, but I digress. This post has nothing to do with Florida or the ocean or cappuccino; I’m just boasting.

This post is the first in a series that covers something that has been in the front of my mind for several years now: lasers. I’ll pause a moment for you to get all of the movie references/jokes about sharks out of your system.

Ok. Lasers are used all over the place: medicine, communications, measurement, meteorology, astronomy, data storage, pointing. The list goes on. But, to paraphrase Jerry Hathaway in Real Genius (watch it right now), “the [laser]. What does it look like?”

Lasers come in many forms, but all have three common ingredients: a power source, gain, and feedback. Each of these will be covered in future posts in more detail. This post is just here to introduce the specimen of study.

My friend and colleague, Mike, had this beauty collecting some dust at his desk.

1980 Gammex He-Ne Laser

1980 Gammex He-Ne Laser

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Cocktails and Drinks

Not One in Twenty

I’ve been reading the book Imbibe! by David Wondrich who I first saw several months back on The Colbert Report. The idea behind the book is that it is a historical and very detailed guide to classic American mixology. The book includes anecdotes and recipes dating back to the mid-1800s or so, through the early 20th century, and presumably beyond (I haven’t finished reading it yet). It invokes images of what must have been a much better time for the social cocktail drinker than now. (That’s cocktail in the lowercase, generic sense; Cocktail refers to a particular drink popular after the Civil War consisting simply of spirits, gum syrup, bitters, and curaçao. [1])

Don’t get me wrong. There are still a lot of good bartenders out there, but many of them, through no fault of their own, must serve drinks made with various pre-mixed potions for the sake of speed and cost and, frankly, because the average customer doesn’t know what he’s missing anymore.

On the other hand, there are some lousy bartenders out there too. Like the one who gave me a Manhattan with soda water in it once. And the one who gave me a Rum Collins which was iridescent green and had sprite or something in it (instead of just rum, lime juice, sugar, and soda water). This is probably why I normally drink beer or straight spirits when I go out; you pretty much always know what you’re going to get.

This post isn’t meant to bash the current state of the Public House though, but rather to tip my hat to my often missed homeland to the east. I’ll do this in the form of a quote from Mr. Wondrich’s book [2].

First, Wondrich quotes Victorian novelist Charles Reade from 1863: “America is fertile in mixtures: what do we not owe her? Sherry Cobbler, Gin Sling, Cocktail, Mint Julep, Brandy Smash, Sudden Death, Eye Openers.” Then he goes on to discuss the state of things today:

What survives? The Julep (once a year anyway), and the Cocktail in the form of the Old-Fashioned (although outside of Wisconsin, not one bar in twenty can make a proper one anymore).

They do make a good Old-Fashioned.

  1. Wondrich, David. Imbibe!. Penguin Group (USA), Inc. 2007. pp. 187–188.
  2. Ibid. p. 123.

Business
Cooking

Take a Number

I was going to write this post last week when I got a sandwich from a shop on campus. It fell off my radar until today when basically the same thing happened again at a different sandwich shop.

“Can I get your first name for the order?”

No. Give me a number. Every time someone asks for my name, I give it to them to move the process along, but invariably it all ends up taking more time than if the computer just gave them a number to give to me. Usually the experience involves some combination of background noise, poor ergonomics in the POS touchscreen, and the cashier just not caring, and I end up with my sandwich and a receipt that says “Frank” or “Rick”. This makes it especially difficult if I’m eating in and have to listen for Frank’s order to be announced over the malfunctioning PA system.

I suppose the counterargument is an attempt by management to make the shop seem more friendly. “People don’t want to be numbers,” Manager Bob might say. To which I simply reply that you’re not assigning me a number. You’re assigning a number to my sandwich. I’m ok with that, and so is my inanimate sandwich. My sandwich’s feelings are not hurt.

When I’m buying a sandwich, it’s all about accuracy and speed. Both of these can be achieved by simply assigning my order a number. And certainly don’t ask for my name and then give me one of those restaurant pagers on top of it. (This happened today.)

I didn’t go into the shop to make friends, and if I’m honest, there’s an old-fashioned—unfortunately this has become the correct adjective—part of me that doesn’t like complete strangers addressing me by my first name.

Maybe from now on, when buying a sandwich, my first name will be “Twenty.” The sandwich will arrive, and the receipt will probably read, “Tony.”

Sports

Wind or Defiance of Nature

I went for a long bike ride today in Minneapolis. I did 35 miles in two hours fifteen minutes. Give or take. I forgot to reset my clock and odometer, but if memory serves, my last ride was about 12 miles in 48 minutes or so.

This was probably the longest bike ride I’ve ever taken in my life. I went south along the river from my house, across the river at Minnehaha park, past all the lakes in south Minneapolis, skirted downtown, went through the U of M east campus, through the St. Paul campus, and back home.

And it was windy the whole time. Sometimes it helped, but toward the end, I swear it was a headwind no matter which direction I was going.

And I got hit in the face by two windborne things: a large bug and a bunch of leaves.

Now I’m sitting at home listening to branches fall out of the trees and hit the house. I’m reminded of a recent conversation I had about home ownership. I made the point that owning a home is an act of defiance against nature. Sometimes you win and sometimes you don’t, but it’s really an act of purest optimism. Some might say hubris, but that’s a bit negative and ruins my point. I like to stick with optimistic and fundamentally human.

The point is that I’m proud to defy nature. I’m happy that I own a house despite the potential for branches falling and chipmunks invading the garage to get bird seed and water getting into the basement (though I fixed that problem; defiance again). I respect what nature can do, but I can’t deny that I have a bit of a smug smile as I look out at the wind (and now rain) while staying warm and dry.

Electrical Engineering
Optics
Physics

Limits

I saw an interesting post in the Physics Today blog a few weeks ago. Not only was the research presented interesting and important, the post brought up a good point about using limits to better understand physical phenomena.

The researchers verified their model by making one of the parameters unrealistically large. The point being that if the simulation is working correctly, and, in this case, the stiffness of the skull material is made extremely high, the pressure spikes seen in the results should go away. And they did.

In my research, I am looking at numerical simulations of diffraction efficiency in multiplexed volume holograms. It is well-known in optics how a single volume grating operates for a given input beam, but it is less well-known what happens when you have two or three or fifty gratings in the same optical element.

Like the research in the post, limits can be used to help verify the model. Instead of making a parameter very large, though, I make a parameter very small. In the case of two simultaneous gratings, if the index modulation (the depth or strength) of one of the gratings is made very small, the results should approach the well-known results for the case where the other grating exists by itself. And they do.

If you’re not sure if your model is working correctly, be sure take some parameters to a limit for which you know what to expect. This won’t necessarily tell you if your model is correct, but it should tell you if it’s wrong.