Qubits can, for instance, transmit coded messages with
absolute secrecy, typically in the form of particles of light,
or photons (SN: 8/16/08, p. 24). Messages sent as a string of
qubits, encoded in the orientations of photon vibrations, are
secure because any attempt at eavesdropping would alter the
message in a detectable way.
Such quantum-secured systems are already commercially available, and may someday be a commercial necessity because of another quantum information application:
quantum computing. For certain problems, computing with
qubits held in a quantum memory can solve mathematical
problems so hard that a standard supercomputer couldn’t
find the answer within the lifetime of the universe. One such
hard problem is finding the prime factors of very big numbers.
Codes based on such problems, which now protect most electronic financial transactions, would be worthless in a world
with full-scale quantum computers. (No need to worry about
your credit card security just yet, though. Breaking today’s
codes would require a quantum computer handling thousands
or more qubits; the record for today’s prototypes is merely 14.)
Quantum computers wouldn’t be worth much for general
number crunching. They would work only for problems that
could be posed in the form of an algorithm amenable to the
way quantum weirdness can cancel out wrong answers, allowing only the correct one to survive. But a sufficiently sophisticated quantum computer would be able to simulate molecular
systems governed by quantum mechanics. You could harness
that power to foretell the outcome of chemical reactions, for
instance, without the bother of test tubes. Such computing
ability could aid the design of new industrial materials or help
develop powerful drugs with fewer side effects.
“Of the currently understood algorithms, the one that
seems most promising for applications is simulation of a
quantum system,” says Caltech physicist John Preskill. “We
don’t currently envision that you’ll be sending your e-mail
on a quantum computer. On the other hand, quantum games
might be a blast.”
But for all these wonders, quantum computers and other
quantum information processing systems are not mere
investment speculation opportunities. They are tools for
scientists to dig deeper into reality’s foundations. Quan-
tum information could reveal nuances about the interface
between mathematics and the physical world.
Cracking codes, for instance, involves solving the very
hard math problem of finding the prime factors of a big
number, hundreds of digits long. But the fact that a quan-tum-computing algorithm can solve such a problem — as
discovered by the mathematician Peter Shor in 1994 — has
deeper implications than just financial eavesdropping.
“Factoring is a hard problem classically,” says Preskill, “but
Shor’s algorithm shows that it is an easy problem quantumly.
And so it seems the boundary between what problems are
hard and what problems are easy is different in our physical
world — because it’s a quantum world — than it would be if the
To solve certain hard problems beyond the ability of ordinary
computers, quantum computers need to process bits of
quantum information, or qubits. One proposed method would
store the qubits in the form of rubidium atoms (red) held in
place by an “optical lattice” (blue) created by laser beams.
world were classical.” In other words, quantum information
processing reveals something about math’s relation to physical reality that prequantum scientists couldn’t have imagined.
Or at least that’s what quantum scientists believe. Prov-
ing that the physical world really does allow quantum solu-
tions to some hard math problems requires actually building
a large-scale quantum computer. “We hope to be able to
verify that these extraordinary computational resources in
quantum systems really are part of the way nature behaves,”
Preskill noted recently in Vancouver at the annual meeting
of the American Association for the Advancement of Science.
“We could do so by solving a problem that we think is hard
classically … with a quantum computer, where we can easily
verify with a classical computer that the quantum computer
got the right answer.”
Factoring would be one example of such a problem — very
hard to solve, but easy to check to see if the answer you get is
right. But other hard math problems probably exceed even
a quantum computer’s capabilities. “Some problems are
quantumly hard,” says Preskill. Knowing which problems are
hard for quantum computers would offer insight into what
kinds of mathematical computations are actually possible in
the physical universe.
One computational claim challenged by quantum computing, MIT computer scientist Scott Aaronson points out, is a
long-held belief called the extended Church-Turing thesis. It
basically states that anything feasibly computable by a physical device is also computable by an idealized “universal”
computer known as a Turing machine.
“This is a falsifiable claim about the laws of physics,”
Aaronson said at the AAAS meeting. It expresses the belief
that if physical laws are like computer code, any reasonable programming language for nature’s laws could emulate