18 research outputs found
Rewindable Quantum Computation and Its Equivalence to Cloning and Adaptive Postselection
We define rewinding operators that invert quantum measurements. Then, we
define complexity classes , , and as
sets of decision problems solvable by polynomial-size quantum circuits with a
polynomial number of rewinding operators, cloning operators, and adaptive
postselections, respectively. Our main result is that . As a
byproduct of this result, we show that any problem in can be
solved with only postselections of outputs whose probabilities are polynomially
close to one. Under the strongly believed assumption that , or the shortest independent vectors problem cannot be
efficiently solved with quantum computers, we also show that a single rewinding
operator is sufficient to achieve tasks that are intractable for quantum
computation. In addition, we consider rewindable Clifford and instantaneous
quantum polynomial time circuits.Comment: 29 pages, 3 figures, v2: Added Result 3 and improved Result
Merlin-Arthur with efficient quantum Merlin and quantum supremacy for the second level of the Fourier hierarchy
We introduce a simple sub-universal quantum computing model, which we call
the Hadamard-classical circuit with one-qubit (HC1Q) model. It consists of a
classical reversible circuit sandwiched by two layers of Hadamard gates, and
therefore it is in the second level of the Fourier hierarchy. We show that
output probability distributions of the HC1Q model cannot be classically
efficiently sampled within a multiplicative error unless the polynomial-time
hierarchy collapses to the second level. The proof technique is different from
those used for previous sub-universal models, such as IQP, Boson Sampling, and
DQC1, and therefore the technique itself might be useful for finding other
sub-universal models that are hard to classically simulate. We also study the
classical verification of quantum computing in the second level of the Fourier
hierarchy. To this end, we define a promise problem, which we call the
probability distribution distinguishability with maximum norm (PDD-Max). It is
a promise problem to decide whether output probability distributions of two
quantum circuits are far apart or close. We show that PDD-Max is BQP-complete,
but if the two circuits are restricted to some types in the second level of the
Fourier hierarchy, such as the HC1Q model or the IQP model, PDD-Max has a
Merlin-Arthur system with quantum polynomial-time Merlin and classical
probabilistic polynomial-time Arthur.Comment: 30 pages, 4 figure
Complexity classification of two-qubit commuting hamiltonians
We classify two-qubit commuting Hamiltonians in terms of their computational
complexity. Suppose one has a two-qubit commuting Hamiltonian H which one can
apply to any pair of qubits, starting in a computational basis state. We prove
a dichotomy theorem: either this model is efficiently classically simulable or
it allows one to sample from probability distributions which cannot be sampled
from classically unless the polynomial hierarchy collapses. Furthermore, the
only simulable Hamiltonians are those which fail to generate entanglement. This
shows that generic two-qubit commuting Hamiltonians can be used to perform
computational tasks which are intractable for classical computers under
plausible assumptions. Our proof makes use of new postselection gadgets and Lie
theory.Comment: 34 page
Sparse Quantum Codes from Quantum Circuits
Sparse quantum codes are analogous to LDPC codes in that their check operators require examining only a constant number of qubits. In contrast to LDPC codes, good sparse quantum codes are not known, and even to encode a single qubit, the best known distance is O(ân log(n)), due to Freedman, Meyer and Luo.
We construct a new family of sparse quantum subsystem codes with minimum distance n[superscript 1 - Δ] for Δ = O(1/âlog n). A variant of these codes exists in D spatial dimensions and has d = n[superscript 1 - Δ - 1/D], nearly saturating a bound due to Bravyi and Terhal.
Our construction is based on a new general method for turning quantum circuits into sparse quantum subsystem codes. Using this prescription, we can map an arbitrary stabilizer code into a new subsystem code with the same distance and number of encoded qubits but where all the generators have constant weight, at the cost of adding some ancilla qubits. With an additional overhead of ancilla qubits, the new code can also be made spatially local.National Science Foundation (U.S.) (Grant CCF-1111382)United States. Army Research Office (Contract W911NF-12-1-0486
Weak-value-amplification analysis beyond the AAV limit of weak measurements
The weak-value (WV) measurement proposed by Aharonov, Albert and Vaidman
(AAV) has attracted a great deal of interest in connection with quantum
metrology. In this work, we extend the analysis beyond the AAV limit and obtain
a few main results. (i) We obtain non-perturbative result for the
signal-to-noise ratio (SNR). In contrast to the AAV's prediction, we find that
the SNR asymptotically gets worse when the AAV's WV becomes large, i.e.,
in the case , where is the measurement strength. (ii) With the
increase of (but also small), we find that the SNR is comparable to the
result under the AAV limit, while both can reach -- actually the former can
slightly exceed -- the SNR of the standard measurement. However, along a
further increase of , the WV technique will become less efficient than the
standard measurement, despite that the postselection probability is increased.
(iii) We find that the Fisher information can characterize the estimate
precision qualitatively well as the SNR, yet their difference will become more
prominent with the increase of . (iv) We carry out analytic expressions of
the SNR in the presence of technical noises and illustrate the particular
advantage of the imaginary WV measurement. The non-perturbative result of the
SNR manifests a favorable range of the noise strength and allows an optimal
determination.Comment: 10 pages, 6figure
Theory of measurement-based quantum computing
In the study of quantum computation, data is represented in terms of linear
operators which form a generalized model of probability, and computations are
most commonly described as products of unitary transformations, which are the
transformations which preserve the quality of the data in a precise sense. This
naturally leads to "unitary circuit models", which are models of computation in
which unitary operators are expressed as a product of "elementary" unitary
transformations. However, unitary transformations can also be effected as a
composition of operations which are not all unitary themselves: the "one-way
measurement model" is one such model of quantum computation.
In this thesis, we examine the relationship between representations of
unitary operators and decompositions of those operators in the one-way
measurement model. In particular, we consider different circumstances under
which a procedure in the one-way measurement model can be described as
simulating a unitary circuit, by considering the combinatorial structures which
are common to unitary circuits and two simple constructions of one-way based
procedures. These structures lead to a characterization of the one-way
measurement patterns which arise from these constructions, which can then be
related to efficiently testable properties of graphs. We also consider how
these characterizations provide automatic techniques for obtaining complete
measurement-based decompositions, from unitary transformations which are
specified by operator expressions bearing a formal resemblance to path
integrals. These techniques are presented as a possible means to devise new
algorithms in the one-way measurement model, independently of algorithms in the
unitary circuit model.Comment: Ph.D. thesis in Combinatorics and Optimization. 199 pages main text,
26 PDF figures. Official electronic version available at
http://hdl.handle.net/10012/413