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The inverse current in coupled (ICC) quantum transport, where one induced current opposes all thermodynamic forces of a system, is a highly counter-intuitive transport phenomenon. Using an exactly solvable model of strongly-coupled quantum dots, we present thermodynamic description of ICC in energy and spin-induced particle currents, with potential applications towards unconventional and autonomous nanoscale thermoelectric generators. Our analysis reveals the connection between microscopic and macroscopic formulations of entropy production rates, elucidating the often-overlooked role of proper thermodynamic forces and conjugate fluxes in characterizing genuine ICC. In our model, the seemingly paradoxical results of ICC in the energy current arise from chemical work done by current-carrying quantum particles, while in spin-induced particle current, it stems from the relative competition between electron reservoirs controlling one particular transition., Comment: 18 pages, 6 figures

We introduce a simplified model for a three-terminal quantum thermocouple consisting of two strongly-coupled quantum dots. To elucidate spin-dependent Seebeck and Peltier effects, we employ a microscopic Hamiltonian and map the Lindblad master equation onto a quantum transition network, capturing the key working principles for both reciprocal effects. Our analysis reveals quantum thermodynamic networks encompassing both Coulomb interaction and spin-flipping processes, lead to the emergence of spin-thermolectric effects. Using algebraic graph theory, we recover the phenomenological law of irreversible thermodynamics from the stochastic version of the entropy production rate expressed in terms of cycle flux and cycle forces. Remarkably, Onsager reciprocity and Kelvin relation for transport coefficients find their premises in the properties of cycle flux trajectories within the quantum transition network. This underscores the universal generality of thermodynamic principles across classical and quantum realms, despite their fundamentally different basis from classical laws of irreversible thermodynamics relying on local equilibrium assumptions., Comment: 19 pages, 6 figures

We introduce a top-ranked cycle flux ranking scheme of network analysis to assess the performance of molecular junction solar cells. By mapping the Lindblad master equation to the quantum-transition network, we propose a microscopic Hamiltonian description underpinning the rate equations commonly used to characterize molecular photocells. Our approach elucidates the paramount significance of edge flux and unveils two pertinent electron transfer pathways that play equally important roles in robust photocurrent generation. Furthermore, we demonstrate that non-radiative loss processes impede the maximum power efficiency of photocells, which may otherwise be above the Curzon-Ahlborn limit. These findings shed light on the intricate functionalities that govern molecular photovoltaics and offer a comprehensive approach to address them in a systematic way., Comment: 14 pages, 8 figures

Recent works on diffusion models have demonstrated a strong capability for conditioning image generation, e.g., text-guided image synthesis. Such success inspires many efforts trying to use large-scale pre-trained diffusion models for tackling a challenging problem--real image editing. Works conducted in this area learn a unique textual token corresponding to several images containing the same object. However, under many circumstances, only one image is available, such as the painting of the Girl with a Pearl Earring. Using existing works on fine-tuning the pre-trained diffusion models with a single image causes severe overfitting issues. The information leakage from the pre-trained diffusion models makes editing can not keep the same content as the given image while creating new features depicted by the language guidance. This work aims to address the problem of single-image editing. We propose a novel model-based guidance built upon the classifier-free guidance so that the knowledge from the model trained on a single image can be distilled into the pre-trained diffusion model, enabling content creation even with one given image. Additionally, we propose a patch-based fine-tuning that can effectively help the model generate images of arbitrary resolution. We provide extensive experiments to validate the design choices of our approach and show promising editing capabilities, including changing style, content addition, and object manipulation. The code is available for research purposes at https://github.com/zhang-zx/SINE.git ., Comment: Project website: https://zhang-zx.github.io/SINE/

We propose a minimal model of a Coulomb coupled fermionic quantum dot thermal diode that can act as an efficient thermal switch and exhibit complete rectification behaviour, even in presence of a small temperature gradient. Using two well defined dimensionless system parameters, universal characteristics of the optimal heat current condition are identified. It is shown to be independent of any system parameter and is obtained only at the mean transitions point "$-0.5$", associated with the equilibrium distribution of the two fermionic reservoirs, tacitly referred to as "$\textit{universal magic mean}$"., Comment: 12 pages, 6 figures , (This article belongs to the Special Issue : Thermodynamics in Quantum and Mesoscopic Systems)

In this article, we show that a quantum gas, a collection of massive, non-interacting, indistinguishable quantum particles can be realized as a thermodynamic machine as an artifact of energy quantization and hence bears no classical analog. Such a thermodynamic machine depends on the statistics of the particles, the chemical potential, and the spatial dimension of the system. Our detailed analysis demonstrates the fundamental features of quantum Stirling cycles from the viewpoint of particle statistics and system dimensions that helps us to realize desired quantum heat engines and refrigerators by exploiting the role of quantum statistical mechanics. In particular, a clear distinction between the behavior of a Fermi gas and a Bose gas is observed in one dimension than in higher dimensions, solely due to the innate differences in their particle statistics indicating the conspicuous role of a quantum thermodynamic signature in lower dimensions.

We apply periodic control to realize a quantum thermal transistor, which we term as the Floquet Quantum thermal Transistor. Periodic modulation allows us to control the heat flows and achieve large amplification factors even for fixed bath temperatures. Importantly, this transistor effect persists in the cut-off region, where traditional quantum thermal transistors operating in absence of periodic modulation, fail to act as viable heat modulation devices., Comment: 16 pages, 12 figures

We have constructed a unified framework for generalizing the finite-time thermodynamic behavior of statistically distinct bosonic and fermionic Stirling cycles with regenerative characteristics. In our formalism, working fluid consisting of particles obeying Fermi-Dirac and Bose-Einstein statistics are treated under equal footing and modelled as a collection of non-interacting harmonic and fermionic oscillators. In terms of frequency and population of the two oscillators, we have provided an interesting generalization for the definitions of heat and work that are valid for classical as well as non-classical working fluids. Based on a generic setting under finite time relaxation dynamics, novel results on low and high temperature heat transfer rates are derived. Characterized by equal power, efficiency, entropy production, cycle time and coefficient of performance, thermodynamic equivalence between two types of Stirling cycles is established in the low temperature "quantum" regime.

The family of group IV-VI monochalcogenides has an atomically puckered layered structure, and their atomic bond configuration suggests the possibility for the realization of various polymorphs. Here, we report the synthesis of the first hexagonal polymorph from the family of group IV-VI monochalcogenides, which is conventionally orthorhombic. Recently predicted four-atomic-thick hexagonal GeSe, so-called {\gamma}-GeSe, is synthesized and clearly identified by complementary structural characterizations, including elemental analysis, electron diffraction, high-resolution transmission electron microscopy imaging, and polarized Raman spectroscopy. The electrical and optical measurements indicate that synthesized {\gamma}-GeSe exhibits high electrical conductivity of 3x10^5 S/m, which is comparable to those of other two-dimensional layered semimetallic crystals. Moreover, {\gamma}-GeSe can be directly grown on h-BN substrates, demonstrating a bottom-up approach for constructing vertical van der Waals heterostructures incorporating {\gamma}-GeSe. The newly identified crystal symmetry of {\gamma}-GeSe warrants further studies on various physical properties of {\gamma}-GeSe., Comment: 24 pages, 5 figures

Based on a system-reservoir model and an appropriate choice of nonlinear coupling, we have explored the microscopic quantum generalization of classical Li\'{e}nard systems. Making use of oscillator coherent states and canonical thermal distributions of the associated c-numbers, we have derived the quantum Langevin equation of the reduced system which admits of single or multiple limit cycles. It has been shown that detailed balance in the form of fluctuation-dissipation relation preserves the dynamical stability of the attractors even in case of vacuum excitation. The quantum versions of Rayleigh, Van der Pol and several other variants of Li\'{e}nard oscillators are derived as special cases in our theoretical scheme within a mean-field description., Comment: Submitted to Physical review E

Training Neural Ordinary Differential Equations (ODEs) is often computationally expensive. Indeed, computing the forward pass of such models involves solving an ODE which can become arbitrarily complex during training. Recent works have shown that regularizing the dynamics of the ODE can partially alleviate this. In this paper we propose a new regularization technique: randomly sampling the end time of the ODE during training. The proposed regularization is simple to implement, has negligible overhead and is effective across a wide variety of tasks. Further, the technique is orthogonal to several other methods proposed to regularize the dynamics of ODEs and as such can be used in conjunction with them. We show through experiments on normalizing flows, time series models and image recognition that the proposed regularization can significantly decrease training time and even improve performance over baseline models., Comment: Neurips 2020

Spin bath polarization is the key to enhancing the sensitivity of quantum sensing and information processing. Significant effort has been invested in identifying the consequences of quantumness and its control for spin-bath polarization. Here, by contrast, we focus on the adverse role of quantum correlations (entanglement) in a spin bath that can impede its cooling in many realistic scenarios. We propose to remove this impediment by modified cooling schemes, incorporating probe-induced disentanglement via alternating, non-commuting probe-bath interactions, so as to suppress the buildup of quantum correlations in the bath. The resulting bath polarization is thereby exponentially enhanced. The underlying thermodynamic principles have far-reaching implications for quantum technological applications, Comment: 5 pages, 3 figures