802 research outputs found
Challenges in Open-air Microwave Quantum Communication and Sensing
Quantum communication is a holy grail to achieve secure communication among a
set of partners, since it is provably unbreakable by physical laws. Quantum
sensing employs quantum entanglement as an extra resource to determine
parameters by either using less resources or attaining a precision unachievable
in classical protocols. A paradigmatic example is the quantum radar, which
allows one to detect an object without being detected oneself, by making use of
the additional asset provided by quantum entanglement to reduce the intensity
of the signal. In the optical regime, impressive technological advances have
been reached in the last years, such as the first quantum communication between
ground and satellites, as well as the first proof-of-principle experiments in
quantum sensing. The development of microwave quantum technologies turned out,
nonetheless, to be more challenging. Here, we will discuss the challenges
regarding the use of microwaves for quantum communication and sensing. Based on
this analysis, we propose a roadmap to achieve real-life applications in these
fields.Comment: Long version of the article published in the Proceeding
Digital-Analog Quantum Simulations with Superconducting Circuits
Quantum simulations consist in the intentional reproduction of physical or
unphysical models into another more controllable quantum system. Beyond
establishing communication vessels between unconnected fields, they promise to
solve complex problems which may be considered as intractable for classical
computers. From a historic perspective, two independent approaches have been
pursued, namely, digital and analog quantum simulations. The former usually
provide universality and flexibility, while the latter allows for better
scalability. Here, we review recent literature merging both paradigms in the
context of superconducting circuits, yielding: digital-analog quantum
simulations. In this manner, we aim at getting the best of both approaches in
the most advanced quantum platform involving superconducting qubits and
microwave transmission lines. The discussed merge of quantum simulation
concepts, digital and analog, may open the possibility in the near future for
outperforming classical computers in relevant problems, enabling the reach of a
quantum advantage.Comment: Review article, 26 pages, 4 figure
Modelling and designing a Paul ion trap
A Paul trap or quadrupole ion trap is a device designed to confine ions or charged particles in a given
space. It consists of four electrodes that produce electric fields varying in time. The voltage applied to these
electrodes varies harmonically with low frequency (quasi-static regime), which simplifies the model. The
goal of this project is to numerically simulate in matlab a Paul trap and the motion of the ions trapped in it
by discretizing the Poisson equation and applying the method of moments (MoM), first in 2D and then
generalized to 3D2019/202
Coplanar Antenna Design for Microwave Entangled Signals Propagating in Open Air
Open-air microwave quantum communication and metrology protocols must be able
to transfer quantum resources from a fridge, where they are created, into an
environment dominated by thermal noise. Indeed, the states that carry such
quantum resources are generated in a cryostat at ~K and with intrinsic impedance, and require an
antenna-like device to transfer them into the open air, characterized by an
intrinsic impedance of and a temperature of
K, with minimal losses. This device accomplishes a
smooth impedance matching between the cryostat and the open air. Here, we study
the transmission of two-mode squeezed thermal states, developing a technique to
design the optimal shape of a coplanar antenna to preserve the entanglement.
Based on a numerical optimization procedure we find the optimal shape of the
impedance is exponential, and we adjust this shape to an analytical function.
Additionally, this study reveals that losses are very sensitive to this shape,
and small changes dramatically affect the outcoming entanglement, which could
have been a limitation in previous experiments employing commercial antennae.
This work will impact the fields of quantum sensing and quantum metrology, as
well as any open-air microwave quantum communication protocol, with special
application to the development of the quantum radar
Digital-analog co-design of the Harrow-Hassidim-Lloyd algorithm
The Harrow-Hassidim-Lloyd quantum algorithm was proposed to solve linear
systems of equations and it is the core of various
applications. However, there is not an explicit quantum circuit for the
subroutine which maps the inverse of the problem matrix into an ancillary
qubit. This makes challenging the implementation in current quantum devices,
forcing us to use hybrid approaches. Here, we propose a systematic manner to
implement this subroutine, which can be adapted to other functions of
the matrix , we present a co-designed quantum processor which reduces the
depth of the algorithm, and we introduce its digital-analog implementation. The
depth of our proposal scales with the precision as
, which is bounded by the number of samples allowed
for a certain experiment. The co-design of the Harrow-Hassidim-Lloyd algorithm
leads to a "kite-like" architecture, which allows us to reduce the number of
required SWAP gates. Finally, merging a co-design quantum processor
architecture with a digital-analog implementation contributes to the reduction
of noise sources during the experimental realization of the algorithm.Comment: 7 pages, 3 figure
Bi-frequency illumination: a quantum-enhanced protocol
We propose a quantum-enhanced sensing protocol to measure the response of a
target object to the frequency of a probe in a noisy and lossy scenario. In our
protocol, a bi-frequency state illuminates a target embedded in a thermal bath,
whose reflectivity is frequency-dependent. After a lossy
interaction with the object, we estimate the parameter in the reflected beam, which captures
information about the response of the object to different electromagnetic
frequencies. Computing the quantum Fisher information relative to the
parameter in an assumed neighborhood of for a
two-mode squeezed state (), and a coherent state (), we show that a
quantum enhancement in the estimation of is obtained when . This quantum advantage grows with the mean reflectivity of the probed
object, and is noise-resilient. We derive explicit formulas for the optimal
observables, and propose a general experimental scheme based on elementary
quantum optical transformations. Furthermore, our work opens the way to
applications in both radar and medical imaging, in particular in the microwave
domain
Quantum Genetic Algorithm with Individuals in Multiple Registers
Genetic algorithms are heuristic optimization techniques inspired by
Darwinian evolution, which are characterized by successfully finding robust
solutions for optimization problems. Here, we propose a subroutine-based
quantum genetic algorithm with individuals codified in independent registers.
This distinctive codification allows our proposal to depict all the fundamental
elements characterizing genetic algorithms, i.e. population-based search with
selection of many individuals, crossover, and mutation. Our subroutine-based
construction permits us to consider several variants of the algorithm. For
instance, we firstly analyze the performance of two different quantum cloning
machines, a key component of the crossover subroutine. Indeed, we study two
paradigmatic examples, namely, the biomimetic cloning of quantum observables
and the Bu\v zek-Hillery universal quantum cloning machine, observing a faster
average convergence of the former, but better final populations of the latter.
Additionally, we analyzed the effect of introducing a mutation subroutine,
concluding a minor impact on the average performance. Furthermore, we introduce
a quantum channel analysis to prove the exponential convergence of our
algorithm and even predict its convergence-ratio. This tool could be extended
to formally prove results on the convergence of general non-unitary
iteration-based algorithms
Quantum vs classical genetic algorithms: A numerical comparison shows faster convergence
Genetic algorithms are heuristic optimization techniques inspired by
Darwinian evolution. Quantum computation is a new computational paradigm which
exploits quantum resources to speed up information processing tasks. Therefore,
it is sensible to explore the potential enhancement in the performance of
genetic algorithms by introducing quantum degrees of freedom. Along this line,
a modular quantum genetic algorithm has recently been proposed, with
individuals encoded in independent registers comprising exchangeable quantum
subroutines [arXiv:2203.15039], which leads to different variants. Here, we
perform a numerical comparison among quantum and classical genetic algorithms,
which was missed in previous literature. In order to isolate the effect of the
quantum resources in the performance, the classical variants have been selected
to resemble the fundamental characteristics of the quantum genetic algorithms.
Under these conditions, we encode an optimization problem in a two-qubit
Hamiltonian and face the problem of finding its ground state. A numerical
analysis based on a sample of 200 random cases shows that some quantum variants
outperform all classical ones in convergence speed towards a near-to-optimal
result. Additionally, we have considered a diagonal Hamiltonian and the
Hamiltonian of the hydrogen molecule to complete the analysis with two relevant
use-cases. If this advantage holds for larger systems, quantum genetic
algorithms would provide a new tool to address optimization problems with
quantum computers.Comment: 7 pages, 4 figures, submitted to the IEEE Symposium Series On
Computational Intelligence 202
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