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quantum Engineering 2020年第3期2卷

作者： Huang, Anqi Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha China

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Experimental review on Majorana zero-modes in hybrid nanowires

arXiv

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arXiv 2020年

作者： Fu, Ji-Bang Li, Bin Zhang, Xin-Fang Yu, Guang-Zheng Huang, Guang-Yao Deng, Ming-Tang Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology NUDT Changsha410073 China

As the condensed matter analog of Majorana fermion, the Majorana zero-mode is well known as a building block of fault-tolerant topological quantum computing. This review focuses on the recent progress of Majorana experiments, especially experiments about semiconductor-superconductor hybrid devices. We first sketch Majorana zero-mode formation from a bottom-up view, which is more suitable for beginners and experimentalists. Then, we survey the status of zero-energy state signatures reported recently, from zero-energy conductance peaks, the oscillations, the quantization, and the interactions with extra degrees of freedom. We also give prospects of future experiments for advancing one-dimensional semiconductor nanowire-superconductor hybrid materials and devices. Copyright © 2020, The Authors. All rights reserved.

关键词： Hybrid materials

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Improved Weak Lensing Photometric Redshift Calibration via StratLearn and Hierarchical Modeling

arXiv

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arXiv 2024年

作者： Autenrieth, Maximilian Wright, Angus H. Trotta, Roberto van Dyk, David A. Stenning, David C. Joachimi, Benjamin Department of Mathematics Imperial College London 180 Queen’s Gate LondonSW7 2AZ United Kingdom German Centre for Cosmological Lensing Bochum44780 Germany SISSA International School for Advanced Studies Via Bonomea 265 Trieste34136 Italy Department of Physics Imperial College London Blackett Laboratory Prince Consort Rd LondonSW72AZ United Kingdom Italian Research Center on High Performance Computing Big Data and Quantum Computing Italy INFN – National Institute for Nuclear Physics Via Valerio 2 Trieste34127 Italy Department of Statistics and Actuarial Science Simon Fraser University Canada Department of Physics and Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom

Discrepancies between cosmological parameter estimates from cosmic shear surveys and from recent Planck cosmic microwave background measurements challenge the ability of the highly successful ΛCDM model to describe the nature of the Universe. To rule out systematic biases in cosmic shear survey analyses, accurate redshift calibration within tomographic bins is key. In this paper, we improve photo-z calibration via Bayesian hierarchical modeling of full galaxy photo-z conditional densities, by employing StratLearn, a recently developed statistical methodology, which accounts for systematic differences in the distribution of the spectroscopic training/source set and the photometric target set. Using realistic simulations that were designed to resemble the KiDS+VIKING-450 dataset, we show that StratLearn-estimated conditional densities improve the galaxy tomographic bin assignment, and that our StratLearn-Bayesian framework leads to nearly unbiased estimates of the target population means. This leads to a factor of ∼ 2 improvement upon the previously best photo-z calibration method. Our approach delivers a maximum bias per tomographic bin of ∆〈z〉 = 0.0095 ± 0.0089, with an average absolute bias of 0.0052 ± 0.0067 across the five tomographic bins. © 2024, CC BY.

关键词： Galaxies

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Randomised benchmarking for characterizing and forecasting correlated processes

arXiv

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arXiv 2023年

作者： Zhang, Xinfang Wu, Zhihao White, Gregory A.L. Xiang, Zhongcheng Hu, Shun Peng, Zhihui Liu, Yong Zheng, Dongning Fu, Xiang Huang, Anqi Poletti, Dario Modi, Kavan Wu, Junjie Deng, Mingtang Guo, Chu Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China School of Physics and Astronomy Monash University VIC3800 Australia Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute of Physics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Science Mathematics and Technology Cluster and Engineering Product Development Pillar Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Centre for Quantum Technologies National University of Singapore 117543 Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit UMI 3654 Singapore Quantum for NSW Sydney2000 Australia

The development of fault-tolerant quantum processors relies on the ability to control noise. A particularly insidious form of noise is temporally correlated or non-Markovian noise. By combining randomized benchmarking with supervised machine learning algorithms, we develop a method to learn the details of temporally correlated noise. In particular, we can learn the time-independent evolution operator of system plus bath and this leads to (i) the ability to characterize the degree of non-Markovianity of the dynamics and (ii) the ability to predict the dynamics of the system even beyond the times we have used to train our model. We exemplify this by implementing our method on a superconducting quantum processor. Our experimental results show a drastic change between the Markovian and non-Markovian regimes for the learning accuracies. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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Coherent ground-state transport of neutral atoms

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Physical Review A 2022年第3期105卷 032417-032417页

作者： X. X. Li J. B. You X. Q. Shao Weibin Li Center for Quantum Sciences and School of Physics Northeast Normal University Changchun 130024 China Institute of High Performance Computing A*STAR (Agency for Science Technology and Research) 1 Fusionopolis Way Connexis Singapore 138632 Center for Advanced Optoelectronic Functional Materials Research and Key Laboratory for UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China School of Physics and Astronomy The University of Nottingham Nottingham NG7 2RD United Kingdom

quantum state transport is an important way to study the energy or information flow. By combining the unconventional Rydberg pumping mechanism and the diagonal form of van der Waals interactions, we construct a theoretical model via second-order perturbation theory to realize a long-range coherent transport inside the ground-state manifold of neutral atoms systems. With the adjustment of the Rabi frequencies and the interatomic distance, this model can be used to simulate various single-body physics phenomena such as a Heisenberg XX spin chain restricted in the single-excitation manifold, coherently perfect quantum state transfer, the parameter-adjustable Su-Schrieffer-Heeger model, and chiral motion of atomic excitation in a triangle by varying the geometrical arrangement of the three atoms, which effectively avoids the influence of atomic spontaneous emission at the same time. Moreover, the influence of atomic position fluctuation on the fidelity of quantum state transmission is discussed in detail, and the corresponding numerical results show that our work provides a robust and easily implemented scheme for quantum state transport with neutral atoms.

关键词： quantum information processing quantum simulation Rydberg atoms & molecules Electric moment Nonperturbative methods Perturbative methods quantum Monte Carlo

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SIDE-real: Supernova Ia Dust Extinction with truncated marginal neural ratio estimation applied to real data

arXiv

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arXiv 2024年

作者： Karchev, Konstantin Grayling, Matthew Boyd, Benjamin M. Trotta, Roberto Mandel, Kaisey S. Weniger, Christoph Via Bonomea 265 TriesteI-34136 Italy Institute of Astronomy Kavli Institute for Cosmology Madingley Road CambridgeCB3 0HA United Kingdom Astrophysics Group Physics Department Blackett Lab Imperial College London Prince Consort Road LondonSW7 2AZ United Kingdom INFN - National Institute for Nuclear Physics Via Valerio 2 TriesteI-34127 Italy Italian Research Center on High-Performance Computing Big Data and Quantum Computing Via Magnanelli 2 BO Casalecchio di RenoI-40033 Italy Statistical Laboratory DPMMS University of Cambridge Wilberforce Road CambridgeCB3 0WB United Kingdom University of Amsterdam Science Park 904 AmsterdamNL-1098 XH Netherlands

We present the first fully simulation-based hierarchical analysis of the light curves of a population of low-redshift type Ia supernovæ (SNæ Ia). Our hardware-accelerated forward model, released in the Python package slicsim, includes stochastic variations of each SN's spectral flux distribution (based on the pre-trained BayeSN model), extinction from dust in the host and in the Milky Way, redshift, and realistic instrumental noise. By utilizing truncated marginal neural ratio estimation (TMNRE), a neural network-enabled simulation-based inference technique, we implicitly marginalize over 4000 latent variables (for a set of ≈100 SNæ Ia) to efficiently infer SN Ia absolute magnitudes and host-galaxy dust properties at the population level while also constraining the parameters of individual objects. Amortization of the inference procedure allows us to obtain coverage guarantees for our results through Bayesian validation and frequentist calibration. Furthermore, we show a detailed comparison to full likelihood-based inference, implemented through Hamiltonian Monte Carlo, on simulated data and then apply TMNRE to the light curves of 86 SNæ Ia from the Carnegie Supernova Project, deriving marginal posteriors in excellent agreement with previous work. Given its ability to accommodate arbitrarily complex extensions to the forward model, e.g. different populations based on host properties, redshift evolution, complicated photometric redshift estimates, selection effects, and non-Ia contamination, without significant modifications to the inference procedure, TMNRE has the potential to become the tool of choice for cosmological parameter inference from future, large SN Ia samples. © 2024, CC BY.

关键词： Supernovae

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Cascade of the delocalization transition in a non-Hermitian interpolating Aubry-André-Fibonacci chain

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Physical Review B 2021年第1期104卷 014202-014202页

作者： Liang-Jun Zhai Guang-Yao Huang Shuai Yin The School of Mathematics and Physics Jiangsu University of Technology Changzhou 213001 China Department of Physics Nanjing University Nanjing 210093 China Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 China School of Physics Sun Yat-Sen University Guangzhou 510275 China

In this paper, the interplay of the non-Herimiticity and the cascade of delocalization transition in a quasiperiodic chain are studied. The study is applied in the non-Hermitian interpolating Aubry-André-Fibonacci (IAAF) model, which combines the non-Hermitian Aubry-André (AA) model and the non-Hermitian Fibonacci model through a varying parameter, and the non-Hermiticity in this model is introduced by nonreciprocal hopping. In the non-Hermitian AA limit, the system undergoes a delocalization transition by tuning the potential strength. At the critical point, the spatial distribution of the critical state shows a self-similar structure with the relative distance between the peaks being the Fibonacci sequence, and the finite-size scaling of the inverse participation ratios (IPRs) of the critical ground state with lattice size L shows that IPRg∝L−0.1189. In the non-Hermitian Fibonacci limit, we find that the system is always in the extended phase. Along the continuous deformation from the non-Hermitian AA model into the non-Hermitian Fibonacci model in the IAAF model, the cascade of the delocalization transition is found, but only a few plateaux appear. Moreover, the self-similar structure of spatial distribution for the critical modes along the cascade transition is also found. In addition, we find that the delocalization transition and the real-complex transition for the excited states happen at almost the same parameter. Our results show that the non-Hermiticity provides an additional knob to control the cascade of the delocalization transition besides the on-site potential.

关键词： Anderson localization Critical phenomena Localization Phase transitions quantum phase transitions

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Dark Matter Halo Parameters from Overheated Exoplanets via Bayesian Hierarchical Inference

arXiv

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arXiv 2024年

作者： Benito, María Karchev, Konstantin Leane, Rebecca K. Põder, Sven Smirnov, Juri Trotta, Roberto Tartu Observatory University of Tartu Observatooriumi 1 Tõravere61602 Estonia Theoretical and Scientific Data Science SISSA Trieste Italy SLAC National Accelerator Laboratory Stanford University StanfordCA94039 United States Kavli Institute for Particle Astrophysics and Cosmology Stanford University StanfordCA94039 United States National Institute of Chemical Physics and Biophysics Rävala 10 Tallinn10143 Estonia Department of Mathematical Sciences University of Liverpool LiverpoolL69 7ZL United Kingdom Imperial College London Physics Department Blackett Laboratory Prince Consort Rd LondonSW7 2AZ United Kingdom Italian Research Center on High Performance Computing Big Data and Quantum Computing & National Institute for Nuclear Physics Sezione di Trieste Italy

Dark Matter (DM) can become captured, deposit annihilation energy, and hence increase the heat flow in exoplanets and brown dwarfs. Detecting such a DM-induced heating in a population of exoplanets in the inner kpc of the Milky Way thus provides potential sensitivity to the galactic DM halo parameters. We develop a Bayesian Hierarchical Model to investigate the feasibility of DM discovery with exoplanets and examine future prospects to recover the spatial distribution of DM in the Milky Way. We reconstruct from mock exoplanet datasets observable parameters such as exoplanet age, temperature, mass, and location, together with DM halo parameters, for representative choices of measurement uncertainty and the number of exoplanets detected. We find that detection of O(100) exoplanets in the inner Galaxy can yield quantitative information on the galactic DM density profile, under the assumption of 10% measurement uncertainty. Even as few as O(10) exoplanets can deliver meaningful sensitivities if the DM density and inner slope are sufficiently large. © 2024, CC BY.

关键词： Hierarchical systems

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Reconstructing the dark energy density in light of DESI BAO observations

arXiv

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arXiv 2025年

作者： Berti, Maria Bellini, Emilio Bonvin, Camille Kunz, Martin Viel, Matteo Zumalacarregui, Miguel Département de Physique Théorique Center for Astroparticle Physics Université de Genève Quai E. Ansermet 24 Genève 4CH-1211 Switzerland Center for Astrophysics and Cosmology University of Nova Gorica Nova Gorica Slovenia INAF Istituto Nazionale di Astrofisica Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 TriesteI-34131 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 TriesteI-34151 Italy SISSA - International School for Advanced Studies Via Bonomea 265 TriesteI-34136 Italy INFN – National Institute for Nuclear Physics Via Valerio 2 TriesteI-34127 Italy Italian Research Center on High Performance Computing Big Data and Quantum Computing Italy Am Mühlenberg 1 Potsdam-GolmD-14476 Germany

In light of the evidence for dynamical dark energy (DE) found from the most recent Dark Energy Spectroscopic Instrument (DESI) baryon acoustic oscillation (BAO) measurements, we perform a non-parametric, model-independent reconstruction of the DE density evolution. To do so, we develop and validate a new framework that reconstructs the DE density through a third-degree piece-wise polynomial interpolation, allowing for direct constraints on its redshift evolution without assuming any specific functional form. The strength of our approach resides in the choice of directly reconstructing the DE density, which provides a more straightforward relation to the distances measured by BAO than the equation of state parameter. We investigate the constraining power of cosmic microwave background (CMB) observations combined with supernovae (SNe) and BAO measurements. In agreement with results from other works, we find a preference for deviations from ΛCDM, with a significance of 2.4σ when using the Dark Energy Survey Year 5 (DESY5) SNe data, and 1.3σ with PantheonPlus. In all the cases we consider, the derived DE equation of state parameter presents evidence for phantom crossing. By investigating potential systematic effects in the low-redshift samples of DESY5 observations, we confirm that correcting for the offset in apparent magnitude with respect to PantheonPlus data, as suggested in previous studies, completely removes the tension. Furthermore, we assess the risk of potentially overfitting the data by changing the number of interpolation nodes. As expected, we find that with lesser nodes we get a smoother reconstructed behavior of the DE density, although with similar overall features. The pipeline developed in this work is ready to be used with future high-precision data to further investigate the evidence for a non-standard background evolution. Copyright © 2025, The Authors. All rights reserved.

关键词： Supernovae

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21cm Intensity Mapping cross-correlation with galaxy surveys: current and forecasted cosmological parameters estimation for the SKAO

arXiv

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arXiv 2023年

作者： Berti, Maria Spinelli, Marta Viel, Matteo SISSA- International School for Advanced Studies Via Bonomea 265 Trieste34136 Italy INFN - National Institute for Nuclear Physics Via Valerio 2 Trieste34127 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy Institute for Particle Physics and Astrophysics ETH Zürich Wolfgang Pauli Strasse 27 Zürich8093 Switzerland INAF Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 TriesteI-34131 Italy Department of Physics and Astronomy University of the Western Cape Robert Sobukhwe Road Bellville7535 South Africa Italian Research Center on High Performance Computing Big Data and Quantum Computing Italy

We present a comprehensive set of forecasts for the cross-correlation signal between 21cm intensity mapping and galaxy redshift surveys. We focus on the data sets that will be provided by the SKAO for the 21cm signal, DESI and Euclid for galaxy clustering. We build a likelihood which takes into account the effect of the beam for the radio observations, the Alcock-Paczynski effect, a simple parameterization of astrophysical nuisances, and fully exploit the tomographic power of such observations in the range z = 0.7 − 1.8 at linear and mildly non-linear scales (k c ℎ2 and H0 is reduced by a factor 3 and 6, respectively, compared to CMB only data, due to the measurement of matter clustering provided by the two observables. The cross-correlation signal has a constraining power that is comparable to the auto-correlation one and combining all the clustering measurements a sub-percent error bar of 0.33% on H0 can be achieved, which is about a factor 2 better than CMB only measurements. Finally, as a proof-of-concept, we test the full pipeline on the real data measured by the MeerKat collaboration (Cunnington et al. 2022) presenting some (weak) constraints on cosmological parameters. Copyright © 2023, The Authors. All rights reserved.

关键词： Signal to noise ratio

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