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Aiming to generalize the label knowledge from a source domain with continuous outputs to an unlabeled target domain, Domain Adaptation Regression (DAR) is developed for complex practical learning problems. However, due to the continuity problem in regression, existing conditional distribution alignment theory and methods with discrete prior, which are proven to be effective in classification settings, are no longer applicable. In this work, focusing on the feasibility problems in DAR, we establish the sufficiency theory for the regression model, which shows the generalization error can be sufficiently dominated by the cross-domain conditional discrepancy. Further, to characterize conditional discrepancy with continuous conditioning variable, a novel Conditional Operator Discrepancy (COD) is proposed, which admits the metric property on conditional distributions via the kernel embedding theory. Finally, to minimize the discrepancy, a COD-based conditional invariant representation learning model is proposed, and the reformulation is derived to show that reasonable modifications on moment statistics can further improve the discriminability of the adaptation model. Extensive experiments on standard DAR datasets verify the validity of theoretical results and the superiority over SOTA DAR methods., Comment: Accepted to ECCV 2024 (oral)

In the NISQ era, achieving large-scale quantum computing demands compact circuits to mitigate decoherence and gate error accumulation. Quantum operations with diverse degrees of freedom hold promise for circuit compression, but conventional approaches encounter challenges in simultaneously adjusting multiple parameters. Here, we propose a transition composite gate (TCG) scheme grounded on state-selective transition path engineering, enabling more expressive conditional operations. We experimentally validate a controlled unitary (CU) gate as an example, with independent and continuous parameters. By adjusting the parameters of $\rm X^{12}$ gate, we obtain the CU family with a fidelity range of 95.2% to 99.0% leveraging quantum process tomography (QPT). To demonstrate the capability of circuit compression, we use TCG scheme to prepare 3-qubit Greenberger-Horne-Zeilinger (GHZ) and W states, with the fidelity of 96.77% and 95.72%. TCG can achieve the reduction in circuit depth of about 40% and 44% compared with the use of CZ gates only. Moreover, we show that short-path TCG (SPTCG) can further reduce the state-preparation circuit time cost. The TCG scheme exhibits advantages in certain quantum circuits and shows significant potential for large-scale quantum algorithms., Comment: 21 pages, 12 figures

In studying secondary gamma-ray emissions from Primordial Black Holes (PBHs), the production of scalar particles like pions and axion-like particles (ALPs) via Hawking radiation is crucial. While previous analyses assumed relativistic production, asteroid-mass PBHs, relevant to upcoming experiments like AMEGO-X, likely produce pions and ALPs non-relativistically when their masses exceed 10 MeV. To account for mass dependence in Hawking radiation, we revisit the greybody factors for massive scalars from Schwarzschild black holes, revealing significant mass corrections to particle production rates compared to the projected AMEGO-X sensitivity. We highlight the importance of considering non-relativistic $\pi^0$ production in interpreting PBH gamma-ray signals, essential for determining PBH properties. Additionally, we comment on the potential suppression of pion production due to form factor effects when producing extended objects via Hawking radiation. We also provide an example code for calculating the Hawking radiation spectrum of massive scalar particles., Comment: 16+2 pages, 8 figures. The numerical code is available at https://github.com/Haoran-Brook/HoRNS

Berry (geometric) phase has attracted a lot of interest and permeated into all aspects of physics including photonics, crystal dynamics, electromagnetism and heat transfer since it was discovered, leading to various unprecedented effects both in classical and quantum systems, such as Hannay angle, quantum Hall effect, orbital magnetism and Thouless pumping. Heat pumping is one of the most prominent and fantastic application of geometric phase in heat transport. Here we derive a general heat pumping theory based on classical diffusion equation and continuous modulation of system parameters in macroscopic thermal diffusion system and obtain a formula which is reminiscent of contact between Berry phase and the Berry curvature. Furthermore, we discuss two cases of non-trivial zero heat flux after one cycle which is fundamentally different from the trivial zero heat flux generated by static zero heat bias in physical nature. Then we analyze the dependence of the effect on the system thermal parameters, including some counterintuitive phenomenon. Finally, under the guidance of this theory, we conduct an experiment to demonstrate the accuracy and effectiveness of our theory and observe the heat pumping effect regardless of the presence and the absence of the thermal bias between two ports of system. In general, our work clearly derives the universal form of heat pumping theory under arbitrary form of the modulation in the macroscopic thermal diffusion system, this is of great significance for better heat energy transport, heat manipulation and so on. It also establishes the foundation of achieving other non-reciprocity devices or topological devices with the aid of spatiotemporal modulation., Comment: 17 pages, 2 figures

The fallback disk model is widely accepted to explain long-period neutron stars (NSs) which can't be simulated by magnetic dipole radiation. However, no confirmed detection of disk was found from the newly discovered long period pulsars GLEAM-X 162759.5-523504.3, GPM J1839-10 and the known slowest isolated NSs 1E 161348-5055. This might be that the disks have either been in noninteracting/inactive state where its emission is too weak to be detected or have been disrupted. In this work, we conduct simulations to examine the lifetime of supernova fallback disks around isolated neutron stars. We assume that the disk's mass varies in a self-similar way and its interaction with the NS occurs only in interacting/active state. Our results reveal that nearly all the interacting lifetimes for the disk are shorter than 0.1 Myr while the existence lifetimes are considerably longer., Comment: Accepted in ApJ, comments are welcome

We explore the potential of detecting parity violation in primordial vector fossils using late-time galaxy spins. Utilizing $N$-body simulations, we use halo spins as a reliable proxy for galaxy spins to investigate how effectively such primordial vectorial parity asymmetry remains in galaxy spins at low redshifts. We develop a novel approach to generate initial conditions with substantial parity asymmetry, while maintaining the initial matter power spectrum unchanged. From the parity broken initial condition and halos evolved from it, we construct the initial spin and halo spin fields, respectively. Focusing on the helicity of these vector fields, we detect substantial asymmetry in the initial spin field as a consequence of parity violation in the primordial vector fossil. In addition, we discover that over $50\%$ of the primordial asymmetry in the initial spin field remains in the late-time halo spin field on a range of scales. Given the tight correlation between halo spins and observable galaxy spins, we expect to detect the current amplitude of vectorial parity asymmetry potentially up to $16\sigma$-level in observation, when utilizing galaxy samples from DESI BGS. Our findings demonstrate that the primordial imprints of vectorial parity violation persist through non-linear gravitational evolution, highlighting the reliability of galaxy spin as a sensitive probe for testing the vectorial parity-invariance in the early Universe., Comment: 5 pages, 3 figures. Submitted to PRL

Quantum computational fluid dynamics (QCFD) offers a promising alternative to classical computational fluid dynamics (CFD) by leveraging quantum algorithms for higher efficiency. This paper introduces a comprehensive QCFD method, including an iterative method "Iterative-QLS" that suppresses error in quantum linear solver, and a subspace method to scale the solution to a larger size. We implement our method on a superconducting quantum computer, demonstrating successful simulations of steady Poiseuille flow and unsteady acoustic wave propagation. The Poiseuille flow simulation achieved a relative error of less than $0.2\%$, and the unsteady acoustic wave simulation solved a 5043-dimensional matrix. We emphasize the utilization of the quantum-classical hybrid approach in applications of near-term quantum computers. By adapting to quantum hardware constraints and offering scalable solutions for large-scale CFD problems, our method paves the way for practical applications of near-term quantum computers in computational science., Comment: 31 pages, 10 figures

The density fields constructed by traditional mass assignment methods are susceptible to irritating discreteness, which hinders morphological measurements of cosmic large-scale structure (LSS) through Minkowski functionals (MFs). For alleviating this issue, fixed-kernel smoothing methods are commonly used in literatures, at the expense of losing substantial structural information. In this work, we propose to measure MFs with Delaunay tessellation field estimation (DTFE) technique, with the goal to maximize extractions of morphological information from sparse tracers. We perform our analyses starting from matter fields and progressively extending to halo fields. At matter field level, we elucidate how discreteness affects the morphological measurements of LSS. Then, by comparing with traditional Gaussian smoothing scheme, we preliminarily showcase the advantages of DTFE for enhancing measurements of MFs from sparse tracers. At halo field level, we first numerically investigate various systematic effects on MFs of DTFE fields, which are induced by finite voxel sizes, halo number densities, halo weightings, and redshift space distortions (RSDs), respectively. Then, we explore the statistical power of MFs measured with DTFE for extracting cosmological information encoded in RSDs. We find that MFs measured with DTFE exhibit improvements by $\sim$ $2$ orders of magnitude in discriminative power for RSD effects and by a factor of $\sim$ $3$-$5$ in constraining power on structure growth rate over the MFs measured with Gaussian smoothing. These findings demonstrate the remarkable enhancements in statistical power of MFs achieved by DTFE, showing enormous application potentials of our method in extracting various key cosmological information from galaxy surveys., Comment: 19 pages, 15 figures, and 1 table; accepted for publication in ApJS

Large scale structures provide valuable information of the primordial perturbations that encode the secrets of the origin of the Universe. It is an essential step to map between observables and their initial coordinates, called Lagrangian space, from which primordial perturbations transfer their information to structures via linear theory. By using numerical simulations and state-of-the-art reconstruction techniques, we report the accuracy of estimating the Lagrangian coordinates of galaxies and galaxy clusters, represented by dark matter halos in various ranges of mass, and study the accuracy of this remapping on the angular momentum (spin) reconstruction. Our work shows that galaxy groups and clusters, represented by halos with mass $\gtrsim 10^{13}M_\odot$, can be accurately remapped to Lagrangian space, and their spin reconstruction errors are dominated by the reconstructed initial gravitational potential. For all mass ranges, the errors of Lagrangian remapping, as well as redshift space distortions, play subdominant roles in estimating their angular momenta. This study explains the low correlation level between observed galaxy spins and reconstructed cosmic initial conditions and illustrates the potential of using angular momenta of cosmic structures to improve the reconstruction of primordial perturbations., Comment: 7 pages, 4 figures, 1 table. Matches the accepted version in Physical Review D

We propose a tensor network approach known as the locally purified density operator (LPDO) to investigate the classification and characterization of symmetry-protected topological (SPT) phases in open quantum systems. We extend the concept of injectivity, originally associated with matrix product states and projected entangled pair states, to LPDOs in $(1+1)D$ and $(2+1)D$ systems, unveiling two distinct types of injectivity conditions inherent in short-range entangled density matrices. Within the LPDO framework, we outline a classification scheme for decohered average symmetry-protected topological (ASPT) phases, consistent with earlier results obtained through spectrum sequence techniques. We first illustrate our framework with ASPT phases protected by fermion parity symmetry, then extend the classification of ASPT phases to a general group extension. We demonstrate examples of explicit construction of fixed-point LPDOs for ASPT phases including intrinsic ASPTs in both $(1+1)D$ and $(2+1)D$ systems., Comment: 27 pages, 5 figures

Galaxy angular momenta (spins) contain valuable cosmological information, complementing their positions and velocities. The baryonic spin direction of galaxies has been probed as a reliable tracer of their host halos and the primordial spin modes. Here we use the TNG100 simulation of the IllustrisTNG project to study the spin magnitude correlations between dark matter, gas, and stellar components of galaxy-halo systems and their evolutions across cosmic history. We find that these components generate similar initial spin magnitudes from the same tidal torque in Lagrangian space. At low redshifts, the gas component still traces the spin magnitude of the dark matter halo and the primordial spin magnitude. However, the traceability of the stellar component depends on the $ex$ $situ$ stellar mass fraction, $f_{\rm acc}$. Our results suggest that the galaxy baryonic spin magnitude can also serve as a tracer of their host halo and the initial perturbations, and the galaxy-halo correlations are affected by the similarity of their evolution histories., Comment: 10 pages, 10 figures. Matches the accepted version in Physical Review D

Under the global low-carbon target, the uneven spatiotemporal distribution of renewable energy resources exacerbates the uncertainty and seasonal power imbalance. Additionally, the issue of an incomplete hydrogen energy chain is widely overlooked in planning models, which hinders the complete analysis of the role of hydrogen in energy systems. Therefore, this paper proposes a high-resolution collaborative planning model for electricity-thermal-hydrogen-coupled energy systems considering both the spatiotemporal distribution characteristics of renewable energy resources and the multi-scale bottom-to-top investment strategy for the complete hydrogen energy chain. Considering the high-resolution system operation flexibility, this paper proposes a hydrogen chain-based fast clustering optimization method that can handle high-dimensional data and multi-time scale operation characteristics. The model optimizes the geographical distribution and capacity configuration of the Northeast China energy system in 2050, with hourly operational characteristics. The planning optimization covered single-energy devices, multi-energy-coupled conversion devices, and electric-hydrogen transmission networks. Last but not least, this paper thoroughly examines the optimal portfolio selection of different hydrogen technologies based on the differences in cost, flexibility, and efficiency. In the Pareto analysis, the proposed model reduces CO2 emissions by 60% with a competitive cost. This paper provides a zero-carbon pathway for multi-energy systems with a cost 4% less than the social cost of carbon $44.6/ton, and the integration of the complete hydrogen energy chain reduces the renewable energy curtailment by 97.0%. Besides, the portfolio selection results indicate that the system favors the SOEC with the highest energy efficiency and the PEMFC with the fastest dynamic response when achieving zero-carbon emissions, Comment: 32 pages, 17 figures

Iceberg melting is a critical factor for climate change, contributing to rising sea levels and climate change. However, the shape of an iceberg is an often neglected aspect of its melting process. Our study investigates the influence of different ice shapes and ambient flow velocities on melt rates by conducting direct numerical simulations. Our study focuses on the ellipsoidal shape, with the aspect ratio as the control parameter. It plays a crucial role in the melting process, resulting in significant variations in the melt rate between different shapes. Without flow, the optimal shape for a minimal melt rate is the disk (2D) or sphere (3D), due to the minimal surface area. However, as the ambient flow velocity increases, the optimal shape changes with the aspect ratio. We find that ice with an elliptical shape (when the long axis is aligned with the flow direction) can melt up to 10\% slower than a circular shape when exposed to flowing water. We provide a quantitative theoretical explanation for this optimal shape, based on the competition between surface area effects and convective heat transfer effects. Our findings provide insight into the interplay between phase transitions and ambient flows, contributing to our understanding of the iceberg melting process and highlighting the need to consider the aspect ratio effect in estimates of iceberg melt rates.

The atomic exchange effect will lead to a significant increase in the probability density of $\beta$ decays below a few keV. This effect is very important for scientific experiments that performed by low-energy electron spectroscopy measurements. However, the atomic exchange effect involves multi-electron interactions, especially for a system with 82 electrons such as lead. Different parameters will lead to different trends in the energy spectrum predicted by the theory, so it is urgent to carry out experimental measurements to provide parameter limits for the theory. The probability increase brought about by the atomic exchange effect is most obvious near 0keV, and the $\beta$ energy spectrum is accurately measured near this energy point, so as to provide constraints for the physical model of atomic exchange. However, it is extremely difficult to measure the $\beta$ energy spectrum at 0keV due to the limitations of electronic noise and internal conversion effects. The excited decay path of $^{210}$Pb was taken as the observation object,by measuring the total energy spectrum of $\beta$ rays and cascaded gamma rays, the precise measurement of the $\beta$ energy spectrum near 0keV has been completed. The analysis of the $\beta$ energy spectrum of $^{210}$Pb gives the following conclusions. The experimental results first verified the theory that the exchange effect causes the probability increase at the low energy end near 0keV. At the same time, the experimental results are higher than the existing predictions of the atomic exchange effect. At least for Pb element, all the electron shells have played a role in improving the probability density of the low end of the $\beta$ energy spectrum. This discovery will promote the theoretical calculation of the $\beta$ energy spectrum of $^{214}$Pb, at the same time, it also indicates that the reactor neutrinos have a higher probability density at the omnipotent end.

The Grains and Oilseeds Index (GOI) and its sub-indices of wheat, maize, soyabeans, rice, and barley are daily price indexes reflect the price changes of the global spot markets of staple agro-food crops. In this paper, we carry out a visibility graph (VG) analysis of the GOI and its five sub-indices. Our findings reveal that the degree distributions of the VGs, except for rice, exhibit exponentially truncated power-law tails, while the rice VG conforms to a power-law tail. The average clustering coefficients of the six VGs are quite large ($>0.5$) and exhibit a nice power-law relation with respect to the average degrees of the VGs. For each VG, the clustering coefficients of nodes are inversely proportional to their degrees for large degrees and are correlated to their degrees as a power law for small degrees. All the six VGs exhibit small-world characteristics. The degree-degree correlation coefficients shows that the VGs for maize and soyabeans indices exhibit weak assortative mixing patterns, while the other four VGs are weakly disassortative. The average nearest neighbor degree functions have similar patterns, and each function shows a more complex mixing pattern which decreases for small degrees, increases for mediate degrees, and decreases again for large degrees., Comment: 16 pages, 9 figures

Neutron stars (NSs) play essential roles in modern astrophysics. Magnetic fields and spin periods of newborn (zero age) NSs have large impact on the further evolution of NSs, which are however poorly explored in observation due to the difficulty of finding newborn NSs. In this work, we aim to infer the magnetic fields and spin periods (Bi and Pi) of zero-age NSs from the observed properties of NS population. We select non-accretion NSs (NANSs) whose evolution is solely determined by magnetic dipole radiation. We find that both Bi and Pi can be described by log-normal distribution and the fitting sensitively depends on our parameters., Comment: 8 pages, 5 figures, accepted for publication in ApJ