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leau
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Conference 10082: Solid State Lasers XXVI: Technology and Devices
SPIE Photonics West 2017
Part of Proceedings of SPIE Vol. 10082 Solid State Lasers XXVI: Technology and Devices
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UTe 2 : a nearly insulating halffilled j =25f 3 heavy fermion metal
Alexander B. Shick, Shinichi Fujimori, Warren E. Pickett
Phys. Rev. B 103, 125136 (2021)
https://doi.org/10.48550/arXiv.2103.11410
Correlated band theory implemented as a combination of density functional theory with exact diagonalization [DFT+U(ED)] of the Anderson impurity term
with Coulomb repulsion U in the open 14orbital 5f shell is applied to UTe 2 . The small gap for U =0, evidence of the halffilled j = 52 subshell of
5f 3 uranium, is converted for U =3 eV to a flat band semimetal with small heavycarrier Fermi surfaces that will make properties sensitive to
pressure, magnetic field, and offstoichiometry, as observed experimentally. Two means of identification from the Green’s function give a mass
enhancement of the order of 12 for already heavy (flat) bands, consistent with the common heavy fermion characterization of UTe 2 . The predicted
Kondo temperature around 100 K matches the experimental values from resistivity. The electric field gradients for the two Te sites are calculated by
DFT+U(ED) to differ by a factor of seven, indicating a strong site distinction, while the anisotropy factor η = 0.18 is similar for all three sites.
The calculated uranium moment < M 2 > 1/2 of 3.5µ B is roughly consistent with the published experimental CurieWeiss values of 2.8µ B and
3.3µ B (which are fielddirection dependent), and the calculated separate spin and orbital moments are remarkably similar to Hund’s rule values for
an f 3 ion. The U =3 eV spectral density is compared with angleintegrated and angleresolved photoemission spectra, with agreement that there is
strong 5f character at, and for several hundred meV below, the Fermi energy. Our results support the picture that the underlying ground state of UTe 2
is that of a halffilled j = 52 subshell with two halffilled m j = ± 2 1 orbitals forming a narrow gap by hybridization, then driven to a conducting
state by configuration mixing (spincharge fluctuations). UTe 2 displays similarities to UPt 3 with its 5f dominated Fermi surfaces rather than a
strongly localized Kondo lattice system.
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[Edited on 2622022 by leau]


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Quantum restricted Boltzmann machine universal for quantum computation
Yusen Wu, Chunyan Wei, Sujuan Qin, Qiaoyan Wen, Fei Gao
https://arxiv.org/abs/2005.11970
https://doi.org/10.48550/arXiv.2005.1197
The challenge posed by the manybody problem in quantum physics originates from the difficulty of describing the nontrivial correlations encoded in
the manybody wave functions with high complexity. Quantum neural network provides a powerful tool to represent the largescale wave function, which
has aroused widespread concern in the quantum superiority era. A significant open problem is what exactly the representational power boundary of the
singlelayer quantum neural network is. In this paper, we design a 2local Hamiltonian and then give a kind of Quantum Restricted Boltzmann Machine
(QRBM, i.e. singlelayer quantum neural network) based on it. The proposed QRBM has the following two salient features. (1) It is proved universal for
implementing quantum computation tasks. (2) It can be efficiently implemented on the Noisy IntermediateScale Quantum (NISQ) devices. We successfully
utilize the proposed QRBM to compute the wave functions for the notable cases of physical interest including the ground state as well as the Gibbs
state (thermal state) of molecules on the superconducting quantum chip. The experimental results illustrate the proposed QRBM can compute the above
wave functions with an acceptable error.
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Quantum Humanities: A First Use Case for QuantumML in Media Science
Johanna Barzen & Frank Leymann
https://doi.org/10.1007/s4235401902432 .
Quantum computers are becoming real. Therefore, it is promising to use their potentials in different applications areas, which includes research in
the humanities.Due to an increasing amount of data that needs to be processed in the digital humanities the use of quantum computers can contribute to
this research area. To give an impression on how beneficial such involvement of quantum computers can be when analyzing data from the humanities, a
use case from the media science is presented. Therefore, both the theoretical basis and the tooling support for analyzing the data from our digital
humanities project MUSE is described. This includes a data analysis pipeline, containing e.g. various approaches for data preparation, feature
engineering, clustering, and classification where several steps can be realized classically, but also supported by quantum computers.
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Feature Learning with Gaussian Restricted Boltzmann Machine for Robust Speech Recognition
Xin Zheng, Zhiyong Wu, Helen Meng, Weifeng Li, Lianhong Cai
https://arxiv.org/abs/1309.6176
In this paper, we first present a new variant of Gaussian restricted Boltzmann machine (GRBM) called multivariate Gaussian restricted Boltzmann
machine (MGRBM), with its definition and learning algorithm. Then we propose using a learned GRBM or MGRBM to extract better features for robust
speech recognition. Our experiments on Aurora2 show that both GRBMextracted and MGRBMextracted feature performs much better than Melfrequency
cepstral coefficient (MFCC) with either HMMGMM or hybrid HMMdeep neural network (DNN) acoustic model, and MGRBMextracted feature is slightly
better.
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An Algorithm of Quantum Restricted Boltzmann Machine Network Based on Quantum Gates and Its Application
Peilin Zhang, Sheng Li and Yu Zhou
https://doi.org/10.1155/2015/756969
We present an algorithm of quantum restricted Boltzmann machine network based on quantum gates. The algorithm is used to initialize the procedure that
adjusts the qubit and weights. After adjusting, the network forms an unsupervised generative model that gives better classification performance than
other discriminative models. In addition, we show how the algorithm can be constructed with quantum circuit for quantum computer.
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Multiorbital spintriplet pairing and spin resonance in the heavyfermion superconductor UTe 2
Lei Che, Haoyu Hu, Christopher Lane, Emilian M. Nica, JianXin Zhu, and Qimiao
https://arxiv.org/abs/2112.14750
https://doi.org/10.48550/arXiv.2112.14750
The heavyfermion system UTe 2 is a candidate for spintriplet superconductivity, which is of considerable interest to quantum engineering. Among the
outstanding issues is the nature of the pairing state. A recent surprising discovery is the observation of a resonance in the spin excitation spectrum
at an antiferromagneticwavevector [C. Duan et al., Nature 600, 636 (2021)], which stands in apparent contrast to the ferromagnetic nature of the
interactions expected in this system. We show how the puzzle can be resolved by a multiorbitalspintriplet pairing constructed from local degrees of
freedom. Because it does not commute with the kinetic part of the Hamiltonian, the pairing contains both intra and inter band terms in the band
basis. We demonstrate that the intraband pairing component naturally yields a spin resonance at the antiferromagnetic wavevector. Our work illustrates
how orbital degrees of freedom can enrich the nature and properties of spintriplet superconductivity of stronglycorrelated quantum materials.
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Implementation of a WalshHadamard Gate in a Superconducting Qutrit
M A Yurtalan, J Shi, M Kononenko, A Lupascu & S Ashhab
DOI: 10.1103/PhysRevLett.125.180504
Phys Rev Lett. 2020 Oct 30;125(18):180504
https://arxiv.org/abs/2003.04879
We have implemented a WalshHadamard gate, which performs a quantum Fourier transform, in a superconducting qutrit. The qutrit is encoded in the
lowest three energy levels of a capacitively shunted flux device, operated at the optimal fluxsymmetry point. We use an efficient decomposition of
the WalshHadamard gate into two unitaries, generated by offdiagonal and diagonal Hamiltonians, respectively. The gate implementation utilizes
simultaneous driving of all three transitions between the three pairs of energy levels of the qutrit, one of which is implemented with a twophoton
process. The gate has a duration of 35 ns and an average fidelity over a representative set of states, including preparation and tomography errors, of
99.2%, characterized with quantumstate tomography. Compensation of acStark and BlochSiegert shifts is essential for reaching high gate fidelities.
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Generalized Optical Signal Processing Based on MultiOperator Metasurfaces Synthesized by Susceptibility Tensors
Ali Momeni, Hamid Rajabalipanah, Ali Abdolali, Karim Achouri
https://doi.org/10.48550/arXiv.1811.02618
https://arxiv.org/abs/1811.02618
This paper theoretically proposes a multichannel functional metasurface computer characterized by Generalized Sheet Transition Conditions (GSTCs) and
surface susceptibility tensors. The study explores a polarization and anglemultiplexed metasurfaces enabling multiple and independent parallel
analog spatial computations when illuminated by differently polarized incident beams from different directions. The proposed synthesis overcomes
substantial restrictions imposed by previous designs such as large architectures arising from the need of additional subblocks, slow responses, and
most importantly, supporting only the even reflection symmetry operations for normal incidences, working for a certain incident angle or polarization,
and executing only single mathematical operation. The versatility of the design is demonstrated in a way that an ultracompact, integrable and planar
metasurfaceassisted platform can execute a variety of optical signal processing operations such as spatial differentiation and integration. It is
demonstrated that a metasurface featuring nonreciprocal property can be thought of as a new paradigm to break the even symmetry of reflection and
perform both even and oddsymmetry mathematical operations at normal incidences. Numerical simulations also illustrate different aspects of
multichannel edge detection scheme through projecting multiple images on the metasurface from different directions. Such appealing findings not only
circumvent the major potential drawbacks of previous designs but also may offer an efficient, easytofabricate, and flexible approach in wavebased
signal processing, edge detection, image contrast enhancement, hidden object detection, and equation solving without any Fourier lens.
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Biology begins to tangle with quantum computing
Vivien Marx
Nat Methods 18, 715–719 (2021).
https://doi.org/10.1038/s4159202101199z
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Quantum circuit architecture search on a superconducting processor
Kehuan Linghu, Yang Qian, Ruixia Wang, MengJun Hu, Zhiyuan Li, Xuegang Li, Huikai Xu, Jingning Zhang, Teng Ma, Peng Zhao, Dong E. Liu, MinHsiu
Hsieh, Xingyao Wu, Yuxuan Du, Dacheng Tao, Yirong Jin & Haifeng Yu
https://arxiv.org/abs/2201.00934
https://doi.org/10.48550/arXiv.2201.00934
Variational quantum algorithms (VQAs) have shown strong evidences to gain provable computational advantages for diverse fields such as finance,
machine learning, and chemistry. However, the heuristic ansatz exploited in modern VQAs is incapable of balancing the tradeoff between expressivity
and trainability, which may lead to the degraded performance when executed on the noisy intermediatescale quantum (NISQ) machines. To address this
issue, here we demonstrate the first proofofprinciple experiment of applying an efficient automatic ansatz design technique, i.e., quantum
architecture search (QAS), to enhance VQAs on an 8qubit superconducting quantum processor. In particular, we apply QAS to tailor the
hardwareefficient ansatz towards classification tasks. Compared with the heuristic ansatze, the ansatz designed by QAS improves test accuracy from
31% to 98%. We further explain this superior performance by visualizing the loss landscape and analyzing effective parameters of all ansatze. Our work
provides concrete guidance for developing variable ansatze to tackle various largescale quantum learning problems with advantages.
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Reciprocal space study of Heisenberg exchange interactions in ferromagnetic metals
I. V. Kashin, A. Gerasimov, V. V. Mazurenko
https://arxiv.org/abs/2112.13016
https://doi.org/10.48550/arXiv.2112.13016
The modern quantum theory of magnetism in solids is getting commonly derived using Green's functions formalism. The popularity draws itself from
remarkable opportunities to capture the microscopic landscape of exchange interactions, starting from a tightbinding representation of the electronic
structure. Indeed, the conventional method of infinitesimal spin rotations, considered in terms of local force theorem, opens vast prospects of
investigations regarding the magnetic environment, as well as pairwise atomic couplings. However, this theoretical concept practically does not devoid
of intrinsic inconsistencies. In particular, naturally expected correspondence between single and pairwise infinitesimal spin rotations is being
numerically revealed to diverge. In this work, we elaborate this question on the model example and canonical case of bcc iron. Our analytical
derivations discovered the principal preference of onsite magnetic precursors if the compositions of individual atomic interactions are in focus. The
problem of extremely slow or even absent spatial convergence while considering metallic compounds was solved by suggesting the original technique,
based on reciprocal space framework. Using fundamental Fourier transforminspired interconnection between suggested technique and traditional spatial
representation, we shed light on symmetry breaking in bcc Fe on the level of orbitally decomposed total exchange surrounding.
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PREPARING FOR QDAY
Davide Castelvecchi
Nature, Vol 602, 10 February 2022 pp 198201
The quantumcomputer revolution could give hackers superpowers. New encryption algorithms will keep them at bay.
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Quantum Computing: How to Address the National Security Risk
Dr. Arthur Herman & Idalia Friedson
2018 Hudson Institute
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