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We studied the Hayden-Preskill thought experiment with the local projective measurement. Compared to the original model, the measurement is applied on the Hawking radiation that was emitted after throwing the quantum diary into the black hole. Within this setup, we explored various aspects of this model, including the information recovery from the black hole, the relation to the black hole final state proposal, the relation between the Yoshida-Kitaev protocol and Petz recovery map, the effects of the decoherence, and the quantum simulations of the decoding protocols. These aspects may provide us new insights into the non-perturbative nature of quantum black holes.

Better forecasts may not lead to better decision-making. To address this challenge, decision-oriented learning (DOL) has been proposed as a new branch of machine learning that replaces traditional statistical loss with a decision loss to form an end-to-end model. Applications of DOL in power systems have been developed in recent years. For renewable-rich power systems, uncertainties propagate through sequential tasks, where traditional statistical-based approaches focus on minimizing statistical errors at intermediate stages but may fail to provide optimal decisions at the final stage. This paper first elaborates on the mismatch between more accurate forecasts and more optimal decisions in the power system caused by statistical-based learning (SBL) and explains how DOL resolves this problem. Secondly, this paper extensively reviews DOL techniques and their applications in power systems while highlighting their pros and cons in relation to SBL. Finally, this paper identifies the challenges to adopt DOL in the energy sector and presents future research directions.

We employ the approach of path integral in the phase space to study the kinetics of state switching associated with black hole phase transitions. Under the assumption that the state switching process of the black hole is described by the stochastic Langevin equation based on the free energy landscape, we derived the Martin-Siggia-Rose-Janssen-de Dominicis (MSRJD) functional and obtained the path integral expression of the transition probability. The MSRJD functional inherently represents the path integral in the phase space, allowing us to extract the effective Hamiltonian for the dynamics of state switching process. By solving the Hamiltonian equations of motion, we obtain the kinetic path in the phase space using an example of the RNAdS black hole. Furthermore, the dominant kinetic path within the configuration space is calculated. We also discuss the kinetic rate by using the functional formalism. Finally, we examine two further examples: Hawking-Page phase transition and Gauss-Bonnet black hole phase transition at the triple point. Our analysis demonstrates that, concerning the Hawking-Page phase transition, while a dominant kinetic path in the phase space from the large SAdS black hole to the thermal AdS space is present, there is no kinetic path for the inverse process. For the Gauss-Bonnet black hole phase transition at the triple point, the state switching processes between the small, the intermediate and the large Gauss-Bonnet black holes constitute a chemical reaction cycle., Comment: More discussions on generalized free energy from York's approach and phase portrait at the critical point, and a brief review of time-dependent Ginzburg-Landau model are added

Despite the success of electric vehicles on land, electrification of maritime ships is challenged by the dilemma of range anxiety and cargo-carrying capacity. The longer range requires larger batteries, which inevitably eat up the precious cargo space and weight. This paper breaks new ground by proposing a coordinated planning model for offshore charging stations (OCSs) and electric ships (ESs), marking a first in this field. Strategically situated OCS can partition a long maritime route into several shorter segments, which in turn lead to smaller batteries and thus larger cargo capacities. The research analyzed the impact of maritime geographical conditions on the placement and sizing process and provided insights into the trade-offs between battery size, cargo-carrying capacity, and the cruising range of different types of electrified ships. Using real Automatic Identification System (AIS) data, we estimated the economic feasibility of the Shanghai-Busan high-traffic maritime route and conducted a sensitivity analysis on factors affecting its economic viability. The results show that installing OCS can significantly reduce the propulsion cost compared with ESs without OCS and traditional internal combustion engine (ICE) ships.

Forecast-then-optimize is a widely-used framework for decision-making problems in power systems. Traditionally, statistical losses have been employed to train forecasting models, but recent research demonstrated that improved decision utility in downstream optimization tasks can be achieved by using decision loss as an alternative. However, the implementation of decision loss in power systems faces challenges in 1) accommodating multi-stage decision-making problems where upstream optimality cannot guarantee final optimality; 2) adapting to dynamic environments such as changing parameters and nature of the problem like continuous or discrete optimization tasks. To this end, this paper proposes a novel adaptive decision-objective loss (ADOL) to address the above challenges. Specifically, ADOL first redefines the decision loss as objective utilities rather than objective loss to eliminate the need to manually set the optimal decision, thus ensuring the globally optimal decision. ADOL enables one-off training in a dynamic environment by introducing additional variables. The differentiability and convexity of ADOL provide useful gradients for forecasting model training in conjunction with continuous and discrete optimization tasks. Experiments are conducted for both linear programming-based and mixed integer linear programming-based power system two-stage dispatching cases with changing costs, and the results show that the proposed ADOL is capable of achieving globally optimal decision-making and adaptability to dynamic environments. The method can be extended to other multi-stage tasks in complex systems.

Galaxy-galaxy strong gravitational lensing (GGSL) is a powerful probe for the formation and evolution of galaxies and cosmology, while the sample size of GGSLs leads to considerable uncertainties and potential bias. The China Space Station Telescope (CSST, to be launched in late 2026) will conduct observations across 17,500 square degrees of the sky, capturing images in the $ugriz$ bands with a spatial resolution comparable to that of the Hubble Space Telescope. We ran a set of Monte Carlo simulations to predict that the CSST's wide-field survey will observe $\sim$160,000 galaxy-galaxy strong lenses over its lifespan, increasing the number of existing galaxy-galaxy strong lens samples by three orders of magnitude. This is comparable to the capabilities of the $\it Euclid$ telescope but with the added benefit of additional color information. Specifically, the CSST can detect strong lenses with Einstein radii about $0.64\pm0.42^{"}$, corresponding to the velocity dispersions of $217.19 \pm 50.55 \, \text{km/s}$. These lenses exhibit a median magnification of $\sim$5. The apparent magnitude of the unlensed sources in the g-band is $25.87 \pm 1.19$. The signal-to-noise ratio of the lensed images covers a range of $\sim 20$ to $\sim 1000$, allowing us to determine the Einstein radius with an accuracy ranging from $\sim 1 \%$ to $\sim 0.1 \%$, ignoring various modeling systematics. Our estimates indicate that CSST can observe rare systems like double source-plane and spiral galaxy lenses. The above selection functions of the CSST strong lensing observation help optimize the strategy of finding and modeling GGSLs., Comment: 17 pages, 14 figures. Accepted by MNRAS

During the early stages of galaxy evolution, a significant fraction of galaxies undergo a transitional phase between the ``blue nugget" systems, which arise from the compaction of large, active star-forming disks, and the ``red nuggets", which are red and passive compact galaxies. These objects are typically only observable with space telescopes, and detailed studies of their size, mass, and stellar population parameters have been conducted on relatively small samples. Strong gravitational lensing can offer a new opportunity to study them in detail, even with ground-based observations. In this study, we present the first 6 \textit{bona fide} sample of strongly lensed post-blue nugget (pBN) galaxies, which were discovered in the Kilo Degree Survey. By using the lensing-magnified luminosity from optical and near-infrared bands, we have derived robust structural and stellar population properties of the multiple images of the background sources. \rui{The pBN galaxies have very small sizes of $\rm R_{eff}<1.3$ kpc, high mass density inside 1 kpc of $ \rm \log (\Sigma_1/M_{\odot} \mathrm{kpc}^{-2})>9.3$, and low specific star formation rates of $\log (\mathrm{sSFR/Gyr})\lesssim0$, The size-mass and $\Sigma_1$-mass relations of this sample are consistent with those of the red nuggets, while their sSFR is close to the lower end of compact star-forming blue nugget systems at the same redshift, suggesting a clear evolutionary link between them., Comment: Accepted for publication in APJ

We try to understand the trends in the mass density slopes as a function of galaxy properties. We use the results from the best Jeans Anisotropic Modelling (JAM) of the integral-field stellar kinematics for near 6000 galaxies from the MaNGA DynPop project, with stellar masses of $10^{9-12}\ {\rm M_{\odot}}$, including both early-type and late-type galaxies. We use the mass-weighted density slopes for the stellar $\overline{\gamma}_*$, dark $\overline{\gamma}_{\rm DM}$, and total $\overline{\gamma}_{\rm T}$ mass from the MaNGA DynPop project. The $\overline{\gamma}_{\rm T}$ approaches a constant value of 2.2 for high $\sigma_{\rm e}$ galaxies, and flattens for lg$(\sigma_{\rm e}/{\rm km\ s^{-1}})\lesssim2.3$, reaching 1.5 for lg$(\sigma_{\rm e}/{\rm km\ s^{-1}})\approx1.8$. The total and stellar slopes track each other tightly, with $\overline{\gamma}_{\rm T}\approx\overline{\gamma}_*-0.174$ over the full $\sigma_{\rm e}$ range. This confirms the dominance of stellar matter within $R_{\rm e}$. We also show that there is no perfect conspiracy between baryonic and dark matter, as $\overline{\gamma}_*$ and $\overline{\gamma}_{\rm DM}$ do not vary inversely within the $\sigma_{\rm e}$ range. We find that the central galaxies from TNG50 and TNG100 simulations do not reproduce the observed galaxy mass distribution, which we attribute to the overestimated dark matter fraction, possibly due to a constant IMF and excessive adiabatic contraction effects in the simulations. Finally, we present the stacked dark matter density profiles and show that they are slightly steeper than the pure dark matter simulation prediction of $\overline{\gamma}_{\rm DM}\approx1$, suggesting moderate adiabatic contraction in the central region of galaxies. Our work demonstrate the power of stellar dynamics modelling for probing the interaction between stellar and dark matter and testing galaxy formation theories., Comment: 17 pages, 14 figures; accepted by MNRAS

In this study, we generalize the work of Farhi, Guth and Guven [Nucl. Phys. B 339 (1990) 417] to include a wormhole effect. We study the influence of the wormhole on the tunneling of the false vacuum bubble. The spherically symmetric bubble has two domain walls. The classical dynamics of each domain wall are constrained by two classically forbidden regions. We find that the wormhole has increased the number of instantons and thus can enhance the tunneling rate. We have analytically derived the formula for the bubble tunneling rate, which is consistent with the result obtained by Farhi, Guth and Guven when the wormhole disappears. We show that the tunneling rate increases with the throat radius of the wormhole. Furthermore, we illustrate that the tunneling rate increases with an increases in the mass of the black hole or the surface tension. In the case where a wormhole exists within a bubble and is connected to another universe, we demonstrate that the bubble can enter into another universe through quantum tunneling.

We study the generalized free energy of the dyonic AdS black hole in an ensemble with varying electric charge $q_E$ and fixed magnetic charge $q_M$. When we adjust the temperature $T$ and the electric potential $\Phi_E$ of the ensemble, the Ricci scalar curvature $R$ and electromagnetic potential $A_u$ usually diverge at the horizon. We regularize them and incorporate the off-shell corrections into the Einstein-Hilbert action. Alternatively, we find that the off-shell corrections can also be obtained by adding a boundary near the horizon to exclude the singularities. Ultimately, we derive the generalized free energy which is consistent with the definition of the thermodynamic relations. Based on the generalized free energy landscape, we can describe the dynamics of state transition as a stochastic process quantified by the Langevin equation. The path integral framework can be formulated to derive the time-dependent trajectory of the order parameter and the time evolution of the transition probability. By comparing the probability with the result of the classical master equation, we attribute the contribution to the probability of one pseudomolecule or antipseudomolecule (the instanton and anti-instanton pair) to the rate of state transition. These results are consistent with the qualitative analysis of the free energy landscape.

Using the final MaNGA sample of 10K galaxies, we investigate the dark matter fraction $f_{\rm DM}$ within one half-light radius $R_{\rm e}$ for about 6K galaxies with good kinematics spanning a wide range of morphologies and stellar velocity dispersion. We employ two techniques to estimate $f_{\rm DM}$: (i) Jeans Anisotropic Modelling (JAM), which performs dark matter decomposition based on stellar kinematics and (ii) comparing the total dynamical mass-to-light ratios $(M/L)_{\rm JAM}$ and $(M_{\ast}/L)_{\rm SPS}$ from Stellar Population Synthesis (SPS). We find that both methods consistently show a significant trend of increasing $f_{\rm DM}$ with decreasing $\sigma_{\rm e}$ and low $f_{\rm DM}$ at larger $\sigma_{\rm e}$. For 235 early-type galaxies with the best models, we explore the variation of stellar initial mass function (IMF) by comparing the stellar mass-to-light ratios from JAM and SPS. We confirm that the stellar mass excess factor $\alpha_{\rm IMF}$ increases with $\sigma_{\rm e}$, consistent with previous studies that reported a transition from Chabrier-like to Salpeter IMF among galaxies. We show that the $\alpha_{\rm IMF}$ trend cannot be driven by $M_{\ast}/L$ or IMF gradients as it persists when allowing for radial gradients in our model. We find no evidence for the total $M/L$ increasing toward the centre. We detect weak positive correlations between $\alpha_{\rm IMF}$ and age, but no correlations with metallicity. We stack galaxy spectra according to their $\alpha_{\rm IMF}$ to search for differences in IMF-sensitive spectral features (e.g. the $\rm Na_{\rm I}$ doublet). We only find marginal evidence for such differences, which casts doubt on the validity of one or both methods to measure the IMF., Comment: 20 pages, 12 figures, 2 tables; Accepted for publication in MNRAS on 22 April 2024

The effective field theory description of a radiating black hole introduces redundant degrees of freedom that necessitate annihilation of those modes at late stages to conserve entropy. The prevailing view is that such effective process can result in information loss unless the redundant states are annihilated in maximally entangled pairs, resembling quantum teleportation. In this Letter, we demonstrate that this view can be relaxed in a new postselection model. We investigate information recoverability in a radiating black hole through the non-unitary dynamics that projects the randomly-selected modes from a scrambling unitary. We show that the model has the merit of producing the von Neumann entropy of black holes consistent with the island formula calculation and that information in the black hole interior can be decoded from the Hawking radiation without loss after the Page time. Moreover, in this model the Page time gains a new interpretation as the transition point between two channels of information transmission when sufficient amounts of effective modes are annihilated inside the horizon. We present two decoding strategies along with their quantum circuit realizations. The experimental verification of the strategies employs 7-qubit IBM quantum processors, demonstrating the viability of these strategies and the potential for quantum processors to probe the black hole interior., Comment: 5 pages. Short version of arXiv:2307.01454