CHAPTER 36

HUT NUMBER TWO was far larger than Alicia’s domain. To enter by the locked door, Champ had to insert his security badge in a slot and have his fingerprint scanned by a device attached to the wall. The interior of the hut was made up of an enormous work area in the middle, with enclosed rooms around the perimeter. Through some of the open doors of these rooms, Sean could see sophisticated machinery and people working with them. On one wall hung a banner that read: “P = NP.”

Sean pointed to it. “What’s that mean?”

Champ hesitated and then said, “It’s an equation representing NP, or nondeterministic polynomial time equaling P or polynomial time. When fully realized, it’ll make E equals MC squared look like a blueprint for a set of Tinkertoys.”

“How so?”

“Polynomial time represents problems that are easy to solve, well, relatively easy. NP-complete problems represent the most difficult problems in the universe.”

“Like how to cure cancer?”

“Not exactly, although who knows what the applications might turn out to be. In fact we have a department here whose sole duty is to determine how newly minted proteins fold up into just the right shape that determines their function in the body. There are trillions of different ways they could fold, and yet most proteins fold up just the right way.”

Sean noted that the man was far more talkative and articulate when it came to areas of his expertise and he intended to press this advantage. “So if they usually get it right, why is understanding how they do it important?”

“Because they don’t always get it right. And when they don’t it can be catastrophic. Alzheimer’s and Mad Cow Disease are examples of proteins blowing the folding sequence. But what I’m really talking about are, for example, the absolute best way for a car to be manufactured, or how to manage the world’s air traffic not in one of the best ways possible, but the best way possible taking into account every conceivable factor. How to take energy from point A to anywhere else with maximum efficiency; or how to get the proverbial traveling salesman on his route in the most optimal way possible. Indeed, with just fifteen cities on his itinerary the poor salesman has more than 650 billion possibilities to consider.

“Did you know that no software in the world comes with a guarantee of being bug-free? Yet if we can solve NP problems it would be possible to send out perfect software every time. And the kicker is, the way the universe is set up, there’s every reason to believe that when you solve one NP problem, you’ve solved them all in one fell swoop. It would be the greatest discovery in history. The Nobel Prize wouldn’t come close to doing the discoverer of it justice.”

“So how come computers can’t do that now?”

“Computers are deterministic creatures, whereas, as the name states, NP problems are nondeterministic. Thus one needs a nondeterministic technology to solve them.”

“And that’s what you’re working on here?”

“Along with a way to factor huge numbers rapidly.”

“Alicia explained the concept to me. She’s attempting to find a shortcut, then nothing is secure anymore and the world as we know it stops. And stopping the world in its tracks is worthy of a Nobel Prize?”

Champ shrugged. “That’s an issue for the politicians, not us humble scientists. Alicia’s research is a long shot at best.” Champ pointed around the room. “Here is where the answer lies. We only have to find it.” He hesitated a moment and said, “Look at this.”

He eagerly led Sean over to an oval table covered in glass. Underneath the glass was a small odd-looking machine.

“What is it?” Sean asked.

“A Turing machine,” Champ replied with a tone of reverence.

“Turing. Like in Monk Turing?”

“No, as in Alan Turing. However, I believe Monk was related, which goes to show there is something to genetics after all. Alan Turing was a true genius who saved millions of lives back during World War II.”

“Was he a doctor?”

“No, Turing was a mathematician, though that word hardly does the man justice. He was assigned to the famed Bletchley Park, outside London.

We’ve named our buildings huts in tribute to the code breakers at Bletchley because that’s the term they used there for their work facilities. Simply put, Turing invented the bombe machine that broke the back of one of the most important German Enigma ciphers. The war in Europe ended at least two years early because of what Turing did. He was also a homosexual. Thank God the govern-ment didn’t find out back then. They would’ve blackballed him and the Allies might have lost the war, the idiots! As it turned out, after the war his homosexuality was discovered, his career ruined and the poor fellow committed suicide. All that talent wasted simply because he liked boys and not girls.”

“And you called this a Turing machine?”

“Yes. Turing hypothesized a universal thinking machine for want of a better description. Though it looks very simple, I can assure you, with the right set of instructions, a Turing machine can take on any problem. All computers today are built along these lines; think of it as very early software. No one can invent a classical computer that is better or more powerful in concept than a Turing machine; you can only build one that performs the steps faster.”

“There’s that word classical again.”

Champ picked up a long, thin glass tube. “And this is the only device in the world that is potentially more powerful than a Turing machine.”

“You showed me that thing when we first met, but didn’t explain what it was.”

“I can tell you, but you won’t understand it.”

“Come on, I’m not stupid,” Sean said irritably.

The other man snapped, “That’s not the point! You won’t understand it because not even I understand it really. The human mind is not meant to function on a subatomic plane. Any physicist that tells you he fully understands the quantum world is lying.”

“So quantum? That’s what we’re talking about here?”

“Specifically subatomic particles that hold the potential for computing power far beyond human comprehension.”

“It doesn’t look like much,” Sean said, glancing at the tube.

Champ slid his finger along it. “In the computer field, it’s said that size matters. At the Los Alamos National Laboratory there is a supercomputer called Blue Mountain. As you undoubtedly know, every PC in the world has a chip. It’s the brain of the computer and has millions of miniature switches chirping language in 1s and 0s. Blue Mountain has over six thousand chips making it a three teraops computer; that means it can perform three trillion operations per second. They use it to simulate the effects of a nuclear blast since the U.S., thankfully, doesn’t explode the damn things for real anymore. However, as powerful as a three teraops machine is, when they tried to reproduce a mere one millionth of a second of a nuclear blast, it took old Blue four months of crunching numbers.”

“Not exactly blazing speed,” Sean commented.

“They’re working on another supercomputer that will render Blue obsolete, a thirty teraops machine code-named Q spread out over an acre of ground. It will be able to perform more calculations in a minute than a human with a calculator could in a billion years and there are plans to build even faster ones. Yet all these computers are no better than the Turing machine; they just take up far more space and cost far more to run. That was the best we could do.” He held up the tube. “Until now.”

“And you’re saying that’s a computer?”

“In its current state it’s a rudimentary device that can do a few calculations, yet that’s quite beside the point. A computer talks in languages of 1s and 0s. Now with a classic computer you’re either a 1 or a