33,256 research outputs found
The Computational Complexity of Linear Optics
We give new evidence that quantum computers -- moreover, rudimentary quantum
computers built entirely out of linear-optical elements -- cannot be
efficiently simulated by classical computers. In particular, we define a model
of computation in which identical photons are generated, sent through a
linear-optical network, then nonadaptively measured to count the number of
photons in each mode. This model is not known or believed to be universal for
quantum computation, and indeed, we discuss the prospects for realizing the
model using current technology. On the other hand, we prove that the model is
able to solve sampling problems and search problems that are classically
intractable under plausible assumptions. Our first result says that, if there
exists a polynomial-time classical algorithm that samples from the same
probability distribution as a linear-optical network, then P^#P=BPP^NP, and
hence the polynomial hierarchy collapses to the third level. Unfortunately,
this result assumes an extremely accurate simulation. Our main result suggests
that even an approximate or noisy classical simulation would already imply a
collapse of the polynomial hierarchy. For this, we need two unproven
conjectures: the "Permanent-of-Gaussians Conjecture", which says that it is
#P-hard to approximate the permanent of a matrix A of independent N(0,1)
Gaussian entries, with high probability over A; and the "Permanent
Anti-Concentration Conjecture", which says that |Per(A)|>=sqrt(n!)/poly(n) with
high probability over A. We present evidence for these conjectures, both of
which seem interesting even apart from our application. This paper does not
assume knowledge of quantum optics. Indeed, part of its goal is to develop the
beautiful theory of noninteracting bosons underlying our model, and its
connection to the permanent function, in a self-contained way accessible to
theoretical computer scientists.Comment: 94 pages, 4 figure
Spatio-angular Minimum-variance Tomographic Controller for Multi-Object Adaptive Optics systems
Multi-object astronomical adaptive-optics (MOAO) is now a mature wide-field
observation mode to enlarge the adaptive-optics-corrected field in a few
specific locations over tens of arc-minutes.
The work-scope provided by open-loop tomography and pupil conjugation is
amenable to a spatio-angular Linear-Quadratic Gaussian (SA-LQG) formulation
aiming to provide enhanced correction across the field with improved
performance over static reconstruction methods and less stringent computational
complexity scaling laws.
Starting from our previous work [1], we use stochastic time-progression
models coupled to approximate sparse measurement operators to outline a
suitable SA-LQG formulation capable of delivering near optimal correction.
Under the spatio-angular framework the wave-fronts are never explicitly
estimated in the volume,providing considerable computational savings on
10m-class telescopes and beyond.
We find that for Raven, a 10m-class MOAO system with two science channels,
the SA-LQG improves the limiting magnitude by two stellar magnitudes when both
Strehl-ratio and Ensquared-energy are used as figures of merit. The
sky-coverage is therefore improved by a factor of 5.Comment: 30 pages, 7 figures, submitted to Applied Optic
Requirement for quantum computation
We identify "proper quantum computation" with computational processes that
cannot be efficiently simulated on a classical computer. For optical quantum
computation, we establish "no-go" theorems for classes of quantum optical
experiments that cannot yield proper quantum computation, and we identify
requirements for optical proper quantum computation that correspond to
violations of assumptions underpinning the no-go theorems.Comment: 11 pages, no figure
Boson sampling with displaced single-photon Fock states versus single-photon-added coherent states---The quantum-classical divide and computational-complexity transitions in linear optics
Boson sampling is a specific quantum computation, which is likely hard to
implement efficiently on a classical computer. The task is to sample the output
photon number distribution of a linear optical interferometric network, which
is fed with single-photon Fock state inputs. A question that has been asked is
if the sampling problems associated with any other input quantum states of
light (other than the Fock states) to a linear optical network and suitable
output detection strategies are also of similar computational complexity as
boson sampling. We consider the states that differ from the Fock states by a
displacement operation, namely the displaced Fock states and the photon-added
coherent states. It is easy to show that the sampling problem associated with
displaced single-photon Fock states and a displaced photon number detection
scheme is in the same complexity class as boson sampling for all values of
displacement. On the other hand, we show that the sampling problem associated
with single-photon-added coherent states and the same displaced photon number
detection scheme demonstrates a computational complexity transition. It
transitions from being just as hard as boson sampling when the input coherent
amplitudes are sufficiently small, to a classically simulatable problem in the
limit of large coherent amplitudes.Comment: 7 pages, 3 figures; published versio
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