Byron didn't know what Neville saw in her either. “Neville's smart,” he said diplomatically. It was true.
So was he.
There was more hair than he needed, even if he saved a bunch for restringing. He coiled it up and left it in his juice can. There was no way he could prove it was Dory's. If he dug up the backyard where the tree fell, where he found the bones, would the rest of the skeleton be there?
The police. He should call the police, but he'd seen Dragnet, and Perry Mason. When he accepted the wig, the hair, he'd become an accessory after the fact. Maybe he was one even before that, because of the bones.
It was odd, but really the only time he wasn't worried about all this was when he worked on the gimbri. By Thanksgiving, it was ready to play.
He brought it out to show to Neville after dinner. “That is a seriously fine piece of work,” said Neville, cradling the gimbri's round leather back. “Smaller than the other one, isn't it?” His big hands could practically cover a basketball. With one long thumb he caressed the strings. They whispered dryly.
* * * *
"You play it with this.” Byron handed him the bow.
He held it awkwardly. Keyboards, reeds, guitar, drums, flute, even accordion: he'd fooled around with plenty of instruments, but nothing resembling a violin. “You sure you want me to?"
It was half-time on the TV, and dark outside already. Through the living room window, yellow light from a street lamp coated the grainy, grey sidewalk, dissolving at its edges like a pointillist's reverie. A night just like this, he'd first seen how pretty Dory was: the little drops of rain in her hair shining, and it stayed nice as a white girl's.
Not like Calliope's. Hers was as naturally nappy as his, worse between her legs. He sneaked a look at her while Byron was showing him how to position the gimbri upright. She was looking straight back at him, her eyes hot and still. Not as pretty as Dory, no, but she let him do things he would never have dreamed of asking of her little sister.
Mr. Moore stood up from the sofa and called to his wife. “Mama, you wanna come see our resident genius's latest invention in action?"
The gimbri screamed, choked, and sighed. “What on earth?” said Mrs. Moore from the kitchen doorway. She shut her eyes and clamped her lips together as if the awful noise was trying to get in through other ways besides her ears.
Neville hung his head and bit his lower lip. He wasn't sure whether he was trying to keep from laughing or crying.
"It spozed to sound like that, Byron?” asked Calliope.
"No,” Neville told her. “My fault.” He picked up the bow from his lap, frowning. His older brother had taken him to a Charles Mingus concert once. He searched his memory for an image of the man embracing his big bass, and mimicked it the best he could.
A sweeter sound emerged. Sweeter, and so much sadder. One singing note, which he raised and lowered slowly. High and yearning. Soft and questioning. With its voice.
With its words.
"I know you mama, miss me since I'm gone;
I know you mama, miss me since I'm gone;
One more thing before I journey on."
Neville turned his head to see if anyone else heard what he was hearing. His hand slipped, and the gimbri sobbed. He turned back to it.
"Lover man, why won't you be true?
Lover man, why won't you ever be true?
She murdered me, and she just might murder you."
He wanted to stop now, but his hands kept moving. He recognized that voice, that tricky hesitance, the tone smooth as smoke. He'd never expected to hear it again.
"I know you daddy, miss me since I'm gone;
I know you daddy, miss me since I'm gone;
One more thing before I journey on.
"I know you cousin, miss me since I'm gone;
I know you cousin, miss me since I'm gone;
It's cause of you I come to sing this song.
"Cruel, cruel sistah, black and white and red;
Cruel, cruel sistah, black and white and red;
You hated me, you had to see me dead.
"Cruel, cruel sistah, red and white and black;
Cruel, cruel sistah, red and white and black;
You killed me and you buried me out back.
"Cruel, cruel sistah, red and black and white;
Cruel, cruel sistah, red and black and white;
You'll be dead yourself before tomorrow night."
Finally, the song was finished. The bow slithered off the gimbri's strings with a sound like a snake leaving. They all looked at one another warily.
Calliope was the first to speak. “It ain't true,” she said. Which meant admitting that something had actually happened.
But they didn't have to believe what the song had said.
Calliope's suicide early the next morning, that they had to believe: her body floating face-down in the cistern, her short rough hair soft as a wet burlap bag. That, and the skeleton the police found behind the retaining wall, with its smashed skull.
It was a double funeral. There was no music.
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Copyright © 2005 by Nisi Shawl.
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Verse
Song of the Harpy's Lover
You have your yellow feather days,
when grace and something subtler plays
about your face, that once no praise
could catch, or match your wanton ways.
ah, the temptation then is great
to feign that what transpired of late
was passing pique not long-term hate,
and I would rise toward that bait
and risk your future dragon cry,
your future screech-owl's shriek deny,
pretend no claws, now hidden, lie
in wait for when things go awry
did I not know what lies beneath,
that lovely smile is mostly teeth.
—William John Watkins
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The Hand Puppet
The fingers of His mind
Move her head, move her arms.
She thinks she channels
A Pharaoh, builder of pyramids,
But He was here before Egypt,
Before the Nile, and uses her imagined
Egyptian for a mask,
A megaphone to mouth lies through
So He can amuse Himself
Watching the smooth apes another
Millennium. What makes
Them funny makes them fleeting;
He knows that He'll outlast
The pyramids, doubts they will.
He'll miss them. Cockroaches
For a billion years? Dull, dull, dull.
—John Alfred Taylor
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The Werewolf's Absolution
Always when he feels the paws forming under his hands,
he reaches for the revolver
and fumbles the six absolutions into their holes.
But always by the time he can load it,
he has no fingers left to pull the trigger.
—William John Watkins
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Pray for the Tiny Monsters
I do not think that we can wipe it clean. Well, or wipe, so fouled
there would be no life.
I don't think the slate is erasable. Well, or the world.
There will be life. Apes to take the place of us,
rats to take the place of apes, and so—I think; rats
in the trees, swinging from branch to branch, chattering,
nesting—waiting their turn as they have done all along.
Or—ratless—back to the mudskipper, moving more surely then
on suddenly less treacherous shore—fins to fingers,
water to air and always a thing of three elements,
shy of fire -
or the angler fish. Yes—the angler, in wait, and d
angling
some bit of itself as bait for the other hungry. Who so
better in place of us? Who so better to prey, godless?
Or if the seas are sullen, unbearing, wombless,
things waiting small will replace these all and every one.
Look! The tiny monsters become large, grand monsters,
look—notochord, look—jaw, look—spine, look—bone, look—
large arching monsters who will find the stony trace
of races past, the Atlantis we will have left behind.
What will they think of us, what will they want of us,
answered?
And what will this new life do with the dwindled world
we leave them? I SHALL BE OIL in a frozen field,
waiting to be burnt back into the air, anointing them
and of them, inheritors of my earth.
Oh, let us pray, let us pray for them—
let us pray for the tiny monsters.
—W. Gregory Stewart
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The Werewolf Escapes His Wife
What is it draws the corners of her mouth
down into points like a pair of fangs,
beside the fear of rising some howling midnight
to half a length of chain snaked in the moonlight,
its last link broken open like a pair of jaws,
the fear he is never coming back,
or the fear that he is?
—William John Watkins
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Thought Experiments: Adventures in Gnarly Computation
Rudy Rucker
Everything Is a Computation
What is reality? One type of answer to this age-old question has the following format: “Everything is .” Over the years I've tried out lots of different ways to fill in the blank: particles, bumps in spacetime, thoughts, mathematical sets, and more. I once had a friend who liked to say, “The universe is made of jokes."
Now there may very well be no correct way to fill in the “Everything is” blank. It could be that reality is fundamentally pluralistic, that is, made of up all kinds of fundamentally incompatible things. Maybe there really isn't any single one underlying substance. But it's interesting to think that perhaps there is.
Lately I've been working to convince myself that everything is a computation. I call this belief universal automatism. Computations are everywhere, once you begin to look at things in a certain way. The weather, plants and animals, your personal thoughts and shifts of mood, society's history and politics—all computations.
One handy aspect of computations is that they occur at all levels and in all sizes. When you say that everything's made of elementary particles, then you need to think of large-scale objects as being made of a zillion tiny things. But computations come in all scales, and an ordinary natural process can be thought of as a single high-level computation.
If I want to say that all sorts of processes are like computations, it's to be expected that my definition of computation must be fairly simple. I go with the following: A computation is a process that obeys finitely describable rules.
People often suppose that a computation has to “find an answer” and then stop. But our general notion of computation allows for computations that run indefinitely. If you think of your life as a kind of computation, it's quite abundantly clear that there's not going to be a final answer and there won't be anything particularly wonderful about having the computation halt! In other words, we often prefer a computation to yield an ongoing sequence of outputs rather than to attain one final output and turn itself off.
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Everything Is a Gnarly Computation
If we suppose that many natural phenomena are in effect computations, the study of computer science can tell us about the kinds of natural phenomena that can occur. Starting in the 1980s, the scientist-entrepreneur Stephen Wolfram did a king-hell job of combing through vast seas of possible computations, getting a handle on the kinds of phenomena that can occur, exploring the computational universe.
Simplifying just a bit, we can say that Wolfram found three kinds of processes: the predictable, the random-looking, and what I term the gnarly. These three fall into a Goldilocks pattern.
Too cold (predictable). Processes that produce no real surprises. This may be because they die out and become constant, or because they're repetitive in some way. The repetitions can be spatial, temporal, or scaled so as to make fractally nested patterns that are nevertheless predictable.
Too hot (random-looking). Processes that are completely scuzzy and messy and dull, like white noise or video snow. The programmer William Gosper used to refer to computational rules of this kind as “seething dog barf.”
Just right (gnarly). Processes that are structured in interesting ways but nonetheless unpredictable. In computations of this kind we see coherent patterns moving around like gliders; these patterns produce large-scale information transport across the space of the computation. Gnarly processes often display patterns at several scales. We find them fun to watch because they tend to appear as if they're alive.
Gnarliness lies between predictability and randomness. It's an interface phenomenon like organic life, poised between crystalline order and messy deliquescence.
Why do I use the world gnarly? Well, the original meaning of “gnarl” was simply “a knot in the wood of a tree.” In California surfer slang, “gnarly” came to be used to describe complicated, rapidly changing surf conditions. And then, by extension, something gnarly came to be anything with surprisingly intricate detail. As a late-arriving and perhaps over-assimilated Californian, I get a kick out of the word.
Clouds, fire, and water are gnarly in the sense of being beautifully intricate, with purposeful-looking but not quite comprehensible patterns. Although the motion of a projectile through empty space would seem to be predictable, if we add in the effects of mutually interacting planets and suns, the calculation may become gnarly. And earthly objects moving through water or air tend to leave turbulent wakes—which very definitely involve gnarly computations.
All living things are gnarly, in that they inevitably do things that are much more complex than one might have expected. The shapes of tree branches are of course the standard example of gnarl. The life cycle of a jellyfish is way gnarly. The wild three-dimensional paths that a humming bird sweeps out are kind of gnarly too, and, if the truth be told, your ears are gnarly as well.
Needless to say, the human mind is gnarly. I've noticed, for instance, that my moods continue to vary even if I manage to behave optimally and think nice correct thoughts about everything. I might suppose that this is because my moods are affected by other factors—such as diet, sleep, exercise, and biochemical processes I'm not even aware of. But a more computationally realistic explanation is simply that my emotional state is the result of a gnarly unpredictable computation, and any hope of full control is a dream.
Still on the topic of psychology, consider trains of thought, the free-flowing and somewhat unpredictable chains of association that the mind produces when left on its own. Note that trains of thoughts need not be formulated in words. When I watch, for instance, a tree branch bobbing in the breeze, my mind plays with the positions of the leaves, following them and automatically making little predictions about their motions. And then the image of the branch might be replaced by a mental image of a tiny man tossed up high into the air. His parachute pops open and he floats down toward a city of lights. I recall the first time I flew into San Jose, and how it reminded me of a great circuit board. I remind myself that I need to see about getting a new computer soon, and then in reaction, I think about going for a bicycle ride. And so on.
Society, too is carrying out gnarly computations. The flow of opinion, the gyrations of the stock markets, the ebb and flow of success, the accumulation of craft and invention—gnarly, dude.
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So W
hat?
If you were to believe all the ads you see, you might imagine that the latest personal computers have access to new, improved methods that lie wholly beyond the abilities of older machines. But computer science tells us that if I'm allowed to equip my old machine with additional memory chips, I can always get it to behave like any new computer.
This carries over to the natural world. Many naturally occurring processes are not only gnarly, they're capable of behaving like any other kind of computation. Wolfram feels that this behavior is very common, and he formulates this notion in the claim that he calls the Principle of Computational Equivalence (PCE): Almost all processes that are not obviously simple can be viewed as computations of equivalent sophistication.
If the PCE is true, then, for instance, a leaf fluttering in the breeze outside my window is as computationally rich a system as my brain. I seem to be a fluttering leaf? Some scientists find this notion an affront. Personally, I find serenity in accepting that the flow of my thoughts and moods is a gnarly computation that's fundamentally the same as a cloud, a flame, or a fluttering leaf. It's soothing to realize that my mind's processes are inherently uncontrollable. Looking at the waving branches of trees calms me down.
But rather than arguing for the full PCE, I think it's worthwhile to formulate a slightly weaker claim, which I call the Principle of Computational Unpredictability (PCU): Most naturally occurring complex computations are unpredictable.
In the PCU, I'm using “unpredictable” in a specific computer-science sense; I'm saying that a computation is unpredictable if there's no fast shortcut way to predict its outcomes. If a computation is unpredictable and you want to know what state it'll be in after, say, a million steps, you pretty much have to crunch out those million steps to find out what's going to happen.
Traditional science is all about finding shortcuts. Physics 101 teaches students to use Newton's laws to predict how far a cannonball will travel when shot into the air at a certain angle and with a certain muzzle-velocity. But, as I mentioned above, in the case of a real object moving through the air, if we want to get full accuracy in describing the object's motions, we need to take the turbulent flow of air into account. At least at certain velocities, flowing fluids are known to produce computationally complex patterns—think of the bumps and ripples that move back and forth along the lip of a waterfall, or of eddies of milk stirred into coffee. So an earthly object's motion will often be carrying out a gnarly computation, and these computations are unpredictable—meaning that the only certain way to get a really detailed prediction of an artillery shell's trajectory through the air is to simulate the motion every step of the way. The computation performed by the physical motion is unpredictable in the sense of not being reducible to a quick shortcut method. (By the way, simulating trajectories was the very purpose for which the U.S. funded the first electronic computer, ENIAC, in 1946, the same year in which I was born.)
Asimov's SF, Oct/Nov 2005 Page 33
