System Size Research Articles

Dielectric properties of nanoconfined water.

The dielectric function of a dipolar liquid exhibits a strong wavenumber dependence in the bulk homogeneous state. Such a behavior seems to suggest the possibility of a strong system size dependence of the dielectric constant (DC) of a nanoconfined liquid, although details have been revealed only recently. The dielectric properties of nanoconfined water, indeed, show a marked sensitivity not only to the size and shape (dielectric boundaries) of confinement but also to the nature of surface-water interactions. For geometries widely studied, namely, water confined in a narrow slit, nanocylinder, and nanospherical cavity, the asymptotic approach to the bulk value of the DC with the increase in confinement size is found to be surprisingly slow. This seems to imply the appearance of a dipolar cross correlation length, much larger than the molecular length-scale of water. In narrow slits and narrow cylinders, the dielectric function becomes both inhomogeneous and anisotropic, and the longitudinal and transverse components display markedly different system size dependencies. This sensitivity can be traced back to the dependence of the DC on the ratio of the mean square dipole moment fluctuation to the volume of the system. The observed sensitivity of collective dipole moment fluctuations to the length scale of confinement points to the possibility of using DC to estimate the orientational correlation length scale, which has been an elusive quantity. Furthermore, the determination of volume also requires special consideration when the system size is in nanoscale. We discuss these and several other interesting issues along with several applications that have emerged in recent years.

Observation of an Inverse Turbulent-Wave Cascade in a Driven Quantum Gas

We observe an inverse turbulent-wave cascade, from small to large length scales, in a driven homogeneous 2D Bose gas. Starting with an equilibrium condensate, we drive the gas isotropically on a length scale much smaller than its size, and observe a nonthermal population of modes with wavelengths larger than the drive one. At long drive times, the gas exhibits a steady nonthermal momentum distribution. At length scales increasing from the drive one to the system size, this distribution features in turn: (i) a power-law spectrum with an exponent close to the analytical result for a particle cascade in weak-wave turbulence, and (ii) a spectrum reminiscent of a nonthermal fixed point associated with universal coarsening in an isolated 2D gas. In further experiments, based on anisotropic driving, we reveal the complete qualitative picture of how the steady-state cascade forms. Published by the American Physical Society 2024

Infinite ground-state degeneracy of a two-dimensional athermal lattice-gas.

I studied the ground state properties and phase behavior of a two-dimensional lattice gas in which hard-core particles can have at most one nearest neighboring occupied site on the square lattice. Monte Carlo simulations in the grand-canonical ensemble showed no apparent signature of singular thermodynamic behavior when the chemical potential was increased. The absence of an ordering phase transition is traced to the large number of ground state configurations the model is endowed, which is due to the impossibility of satisfying simultaneously closest packing around a vacancy and around a particle. Numerical simulations confirm that the ground state entropy is proportional to the square root of system size.

Refined cyclic renormalization group in Russian doll model

Focusing on Bethe-Ansatz integrable models, robust to both time-reversal symmetry breaking and disorder, we consider the Russian Doll Model (RDM) for finite system sizes and energy levels. Suggested as a time-reversal-symmetry breaking deformation of Richardson’s model, the well-known and simplest model of superconductivity, RDM revealed an unusual cyclic renormalization group (RG) over the system size NN, where the energy levels repeat themselves, shifted by one after a finite period in \ln NlnN, supplemented by a hierarchy of superconducting condensates, with the superconducting gaps following the so-called Efimov (exponential) scaling. The equidistant single-particle spectrum of RDM made the above Efimov scaling and cyclic RG to be asymptotically exact in the wideband limit of the diagonal potential. Here, we generalize this observation in various respects. We find that, beyond the wideband limit, when the entire spectrum is considered, the periodicity of the spectrum is not constant, but appears to be energy-dependent. Moreover, we resolve the apparent paradox of shift in the spectrum by a single level after the RG period, despite the disappearance of a finite fraction of energy levels. We also analyze the effects of disorder in the diagonal potential on the above periodicity and show that it survives only for high energies beyond the energy interval of the disorder amplitude. Our analytic analysis is supported with exact diagonalization.

Managing singular kernels and logarithmic corrections in the staggered six-vertex model

In this paper, we investigate the spectral properties of the staggered six-vertex model with Z2 symmetry for arbitrary system sizes L using non-linear integral equations (NLIEs). Our study is motivated by two key questions: what is the accuracy of results based on the ODE/IQFT correspondence in the asymptotic regime of large system sizes, and what is the optimal approach based on NLIE for analyzing the staggered six-vertex model?We demonstrate that the quantization conditions for low-lying primary and descendant states, derived from the ODE/IQFT approach in the scaling limit, are impressively accurate even for relatively small system sizes. Specifically, in the anisotropy parameter range π/4 < γ < π/2, the difference between NLIE and ODE/IQFT results for energy and quasi-momentum eigenvalues is of order OL−2.Furthermore, we present a unifying framework for NLIEs, distinguishing between versions with singular and regular kernels. We provide a compact derivation of NLIE with a singular kernel, followed by an equivalent set with a regular kernel. We address the stability issues in numerical treatments and offer solutions to achieve high-accuracy results, validating our approach for system sizes ranging from L = 2 to L = 1024.Our findings not only validate the ODE/IQFT approach for finite system sizes but also enhance the understanding of NLIEs in the context of the staggered six-vertex model. We hope the insights gained from this study have significant implications for resolving the spectral problem of other lattice systems with emergent non-compact degrees of freedom and provide a foundation for future research in this domain.

Design of a dual-band common aperture confocal plane optical system

In order to achieve high-quality imaging while simplifying the structure and reducing the size of the optical system, a miniature dual-disc folding reflection optical system was designed. A design approach incorporating reflector fitting is employed; the adjacent reflector is fitted to one mirror. The optimized optical system contains two mirrors, and the system length-to-focal-length ratio is 0.325, which significantly reduces the axial distance of the system. Furthermore, the engineering of the optical system was successfully achieved. The experimental results demonstrate that the captured images display consistent clarity, are free from distortion, and meet the specified design requirements.

Complexity is not enough for randomness

We study the dynamical generation of randomness in Brownian systems as a function of the degree of locality of the Hamiltonian. We first express the trace distance to a unitary design for these systems in terms of an effective equilibrium thermal partition function, and provide a set of conditions that guarantee a linear time to design. We relate the trace distance to design to spectral properties of the time-evolution operator. We apply these considerations to the Brownian pp-SYK model as a function of the degree of locality pp. We show that the time to design is linear, with a slope proportional to 1/p1/p. We corroborate that when pp is of order the system size this reproduces the behavior of a completely non-local Brownian model of random matrices. For the random matrix model, we reinterpret these results from the point of view of classical Brownian motion in the unitary manifold. Therefore, we find that the generation of randomness typically persists for exponentially long times in the system size, even for systems governed by highly non-local time-dependent Hamiltonians. We conjecture this to be a general property: there is no efficient way to generate approximate Haar random unitaries dynamically, unless a large degree of fine-tuning is present in the ensemble of time-dependent Hamiltonians. We contrast the slow generation of randomness to the growth of quantum complexity of the time-evolution operator. Using known bounds on circuit complexity for unitary designs, we obtain a lower bound determining that complexity grows at least linearly in time for Brownian systems. We argue that these bounds on circuit complexity are far from tight and that complexity grows at a much faster rate, at least for non-local systems.

Asymmetrically Fused Nanographene‐Porphyrin Architectures

AbstractA strategy to combine three standalone aromatic building blocks in one coherent, fully conjugated molecule is presented. Namely, benzene, pyrene, and hexa‐peri‐hexabenzocoronene (HBC) are assembled around a central porphyrin core in an ABAC type of geometry and interconnected under oxidative Scholl conditions to achieve merging of the individual π‐systems. The three asymmetric porphyrin conjugates obtained this way exhibit intriguing absorption features, namely strongly red‐shifted and broadened spectra. The presented series of molecules demonstrates the ability to control and influence these optical properties with high precision by altering the size of the aromatic system in a controlled manner. Density functional theory calculations gave more profound insights into the electronic structure and optical transitions of the investigated fused architectures.

Search for the Critical Point via Intermittency Analysis in NA61/SHINE

The existence and location of the QCD critical point are objects of both experimental and theoretical studies. The comprehensive data collected by NA61/SHINE during a two-dimensional scan in beam momentum and system size allows for a systematic search for the critical point – a search for a non-monotonic dependence of various correlation and fluctuation observables on collision energy and size of colliding nuclei. Intermittency analysis is a statistical tool used in heavy ion collisions that includes the study of scaled factorial moments (SFMs) of multiplicity distributions in the 2D transverse momentum space to detect power-law fluctuations and explore different aspects of the QCD phase diagram. In particular, proton intermittency has been used to locate the critical point of strongly interacting matter, and, more recently, intermittency of negatively charged hadrons have also been used to study the properties of QCD interactions.

Approximating Many-Body Quantum States with Quantum Circuits and Measurements

We introduce protocols to prepare many-body quantum states with quantum circuits assisted by local operations and classical communication. We show that by lifting the requirement of exact preparation, one can substantially save resources. In particular, the so-called W and, more generally, Dicke states require a circuit depth and number of ancillas per site that are independent of the system size. As a by-product of our work, we introduce an efficient scheme to implement certain nonlocal, non-Clifford unitary operators. We also discuss how similar ideas may be applied in the preparation of eigenstates of well-known spin models, both free and interacting. Published by the American Physical Society 2024

Rationally independent free fermions with local hopping

Rationally independent free fermions are those where sums of single-particle energies multiplied by arbitrary rational coefficients vanish only if the coefficients are all zero. This property guaranties that they have no degeneracies in the many-body spectrum and gives them relaxation properties more similar to those of generic systems. Using classic results from number theory we provide minimal examples of rationally independent free fermion models for every system size in one dimension. This is accomplished by considering a free fermion model with a chemical potential, and hopping terms corresponding to all the divisors of the number of sites, each one with an incommensurate complex amplitude. We then move on to discuss the many-body spectral statistics for these models. Indeed, because of their nondegenerate spectrum, these systems are potentially compatible with Poissonian spectral statistics, as opposed to most noninteracting systems. We show that local probes—like the ratio of consecutive level spacings—look very similar to what is expected for the Poisson statistics. We however demonstrate that free fermion models can never have Poisson statistics with an analysis of the moments of the spectral form factor. Published by the American Physical Society 2024

Adaptive connectivity control in networked multi-agent systems: A distributed approach.

Effective communication is crucial for the performance and collaboration within cooperative networked multi-agent systems. However, existing literature lacks comprehensive solutions for dynamically monitoring and adjusting communication topologies to balance connectivity and energy efficiency. This study addresses this gap by proposing a distributed approach for estimating and controlling system connectivity over time. We introduce a modified consensus protocol where agents exchange local assessments of communication link quality, enabling the estimation of a global weighted adjacency matrix without requiring centralized information. The system's connectivity is measured using the second smallest eigenvalue of the communication graph Laplacian, commonly referred to as algebraic connectivity. Additionally, we enhance the consensus protocol with an adaptive mechanism to expedite convergence, irrespective of system size or structure. Furthermore, we present an analytical method for connectivity control based on the Fiedler vector approximation, facilitating the addition or removal of communication links. This method adjusts control parameters to accommodate minor variations in link quality while reconfiguring the network in response to significant changes. Notably, it identifies and eliminates energy-consuming yet non-contributory links, improving long-term connectivity efficiency. Simulation experiments across diverse scenarios and the number of agents validate the efficacy of our proposed algebraic connectivity estimation and tracking strategy. Results demonstrate robust connectivity maintenance against external disturbances and agent failures, underscoring the practical utility of our approach for real-world multi-agent systems.

Impact of Corner‐Bridge Flow on Capillary Pressure Curve: Insights From Microfluidic Experiments and Pore‐Network Modeling

AbstractThe capillary pressure curve is essential for predicting multiphase flow processes in geological systems. At low saturations, wetting films form and become important, but how wetting films control this curve remains inadequately understood. In this study, we combine microfluidic experiments with pore‐network modeling to investigate the impact of corner‐bridge flow on the capillary pressure curve in porous media. Using a CMOS camera and a confocal laser scanning microscopy, we directly observe the corner‐bridge flow under quasi‐static drainage displacement, revealing that corner‐bridge flow serves as an additional flow path to drain trapped water. Consequently, the capillary pressure curve shifts toward lower saturations, resulting in a reduced water residual saturation. We establish a theoretical criterion for the occurrence of corner‐bridge flow and develop a pore‐network model to simulate quasi‐static drainage, taking into account this additional flow path. Pore‐network modeling results agree well with our experimental observation. On this basis, we employ our pore‐network model to systematically analyze the impact of corner‐bridge flow on capillary pressure curve across varying porosity, pore‐scale disorder, and system size. Results indicate that the impact of corner‐bridge flow becomes more pronounced as porosity decreases and shape factor increases. Our findings demonstrate that the maximum decrease of water residual saturation is 0.19 when porosity is at its minimum, and the shape factor is at its maximum. This work bridges the gap between the pore‐scale mechanism and capillary pressure behavior and has significant implications for estimating the amount of extractable water and the CO2 storage capacity.

PolyPal: A parallel microscale virtual specimen generator

We present an open source program, PolyPal, that can generate a polycrystalline virtual specimen in the micrometer scale for atomistic calculations and visualization. Unlike regular meshes or perfect lattices, atomic positions in polycrystalline materials need to be defined before calculations, and the capability of an atom-generation code is evaluated by the maximum size of the virtual specimen it can generate as well as by the efficiency of the necessary input-output process. Present atom-generation codes are implemented in a serial fashion, and the maximum size of the virtual specimen is limited by the on-board memory. Furthermore, it is difficult to handle a single position file with billions of atoms not only because it takes a long time to read in a row but also full domain decomposition takes hours. PolyPal addresses these challenges with a fully parallelized MPI input-output scheme that supports multiple export options on a Linux cluster. It has no limit in the system size with virtually perfect scalability. Additionally by controlling the size distribution and homogeneity of grains, the program can simulate different microstructures, as typically found in the bulk system or in thin-film samples, prepared with different fabrication processes. PolyPal will harness molecular dynamics codes in the coming age of the exascale computing. Program summaryProgram Title: PolyPalCPC Library link to program files:https://doi.org/10.17632/5cpbmrtzbr.1Developer's repository link:https://gitlab.com/GeonbuShin/polypal.gitLicensing provisions: GPLv3Programming language: C++Nature of problem: There is no open source code capable of generating massive polycyrstalline microstructures that contain billions of atoms. Existing codes run in a single thread, and hence, have a system size limited by the memory resources. Also, a single input/output filestream is not appropriate for a system with a large amount of atoms as file reading and writing would take a prohibitively long time, working as a bottleneck.Solution method: PolyPal not only creates atomic structures in parallel but also writes positions to multiple files in parallel within the Message Passing Interface (MPI). The parallel computing feature not only enables access to micrometer-scale atomic systems but also accelerates the entire process from atomic generation to file generation. In this code, each subdomain is filled with atoms simultaneously according to the prescribed domain topology with inherent load balancing. The atomic structure is written out to multiple files in parallel; one structure file is generated for each domain assigned to the corresponding node of a computing cluster via MPI-IO, which drastically reduces the input-output time, and makes it possible to handle a large virtual specimen.Additional comments including restrictions and unusual features: PolyPal can generate a layered polycrystalline structure to mimic a thin-film specimen prepared by deposition. The code utilizes MPI-IO to accelerate file output.

A novel eight-switch nine-level modified ANPC inverter topology and its optimal modulation strategy

An eight-switch nine-level modified ANPC inverter (8S-9L-MANPC) is designed and simulated in this paper. With this topology, only one DC voltage source and eight active semiconductor switches are required, significantly reducing system size, weight, and cost. The structure consists of a five-level ANPC inverter cascaded with a two-level leg converter. This arrangement extends the 5L-ANPC structure to a 9L configuration without requiring the use of additional capacitors. To maintain the balancing of the flying capacitor (FC), a modulation strategy using a switching state redundancy-based control method is employed. Recent 9L inverters incorporating flying capacitors and based on a hybrid structure have been compared with the proposed structure. By conducting this comparison, we can highlight the potential improvements offered by the proposed structure over the recent 9L inverters in terms of reduced component count, simplified design, and cost savings. The proposed 8S-9L-MANPC inverter is tested under various operating situations in MATLAB/Simulink simulation.

Quantum neural networks to detect entanglement transitions in quantum many-body systems

Abstract Quantum entanglement becomes increasingly complex to analyze in many-body systems due to exponential growth in complexity with system size. In this work, we explore the potential of quantum machine learning (QML) to circumvent this. Specifically, we train a parameterized quantum neural network (QNN) model to detect transitions in the entanglement properties of the ground state in a multi-spin Ising model. This approach enables the classification of different entanglement states and provides deeper insights into the behavior of entanglement under multi-spin interactions. Our results demonstrate that QML can effectively simplify the classification process and overcome the complexity challenges encountered by classical algorithms.

Size scalability of Monte Carlo simulations applied to oxidized polypyrrole systems

Oxidized polypyrrole (PPy) is a conducting polymer with diverse applications such as supercapacitors, sensors, batteries, actuators, neural prosthetics, among others. PPy is most commonly synthesized for the specific application yielding low molecular weight oligomers that form amorphous polymer matrices. Hence, molecular simulation analyses are challenging. This work generalizes the recently proposed coarse grained force field (CGFF) for halogen oxidized PPy in the condensed phases and introduces a novel implementation of the Monte Carlo (MC) simulation based on the CGFF that enables simulations of polymer systems with more than 100000 particles. The MC implementation utilizes a combination of CPU and GPUs and exploits a numerical approximation based on polynomial piecewise interpolation for the calculation of the CGFF pairwise additive terms. The MC simulations evidence that the oxidized PPy thermodynamic and structural properties are consistent as the system size is scaled up. Predicted properties include density, enthalpy, potential energy, heat capacity, coefficient of thermal expansion, caloric curve, glass transition temperature range, compressibility, bulk modulus, radial distribution functions, and polymer chain characteristics. The oxidized PPy samples display oligomer chain stacking that persists with temperatures up to the glass transition. Simulated properties are consistent with experimental observations when available and predict trends in all other cases.

Sequence stratigraphic framework of carbonates in mixed siliciclastic–carbonate sequences: local versus external controls in a tectonically active basin (Lorca Basin, Miocene, SE Spain)

ABSTRACT The sequence stratigraphic framework of initiation and growth of carbonates in environments impacted by siliciclastic inputs is highly variable because of the biogenic nature of the sedimentary production and its sensitivity to environmental conditions. Using panorama interpretations, logging, and characterization of benthic communities, the mixed carbonate–siliciclastic sedimentary succession of the Neogene Lorca Basin (SE Spain) has been studied to decipher the role of local and global controlling parameters on the sequence stratigraphic framework of carbonate production. Three different carbonate depositional models are distinguished: 1) retrogradational homoclinal ramps (type 1) dominated by heterozoan communities that developed lateral to alluvial fans, 2) progradational flat-topped coral platforms (type 2) with Porites and Tarbellastraea coral carpets with a coeval retrogradational pattern on basin margins, and 3) retrogradational narrow siliciclastic-rich coral platforms (type 3) with Tarbellastraea buildups intercalated with deltaic deposits. Onset of carbonate production systematically occurred during transgressions controlled by eustasy and was locally enhanced by extensional tectonics. In steep margins located in the vicinity of major marginal faults, transgressions were characterized by high terrigenous inputs, and only heterozoan-dominated ramps (type 1) developed. The flooding of these steep and tectonically active margins characterized by small drainage basins and immature, locally sourced alluvial systems led to lower terrigenous fluxes and the growth of coral flat-topped platforms (type 2) during subsequent highstands. Away from main marginal faults, deltaic environments were sourced by large drainage basins. They were characterized by a flat topography that permitted the occurrence of a shallow photic zone subject to low and irregular terrigenous inputs up to the distal part of the depositional profile during transgressions. In this deltaic configuration, the growth of narrow siliciclastic-rich coral platforms (type 3) were favored. On these platforms, coral buildups were regularly buried by terrigenous inputs during highstands. In the Lorca Basin, the dimensions of siliciclastic systems and the size of their drainage basins also directly impacted the sequence stratigraphic framework of carbonates intercalated in terrigenous units. This study illustrates the marked variability in: 1) the different types of carbonate depositional profiles and 2) the timing of these carbonates in a mixed carbonate–siliciclastic system because of the size, maturity, and location of siliciclastic systems, local tectonics, inherited topography, and global sea-level fluctuations.

Integrating Self-Initialized Local Thermalizing Lindblad Operators for Variational Quantum Algorithm with Quantum Jump: Implementation and Performance.

Quantum computing holds great potential for simulating quantum systems, such as molecular systems, due to its inherent ability to represent and manipulate quantum states. However, simulating nonunitary dynamics of open quantum systems on a quantum computer is still challenging. Here, we present a scheme denoted as VQS-QJ-LTLME, which adopts the trajectory average of quantum jump Monte Carlo wave function variational evolution to evolve the system's density matrix and local thermalizing Lindblad operators to describe the system-environment interactions. This combination allows the quantum circuit to be initialized after a period of evolution, thereby eliminating the accumulation of errors. The VQS-QJ-LTLME algorithm requires only log2(n) qubits for system size n and holds a time complexity of , making it particularly suitable for operation on noisy intermediate-scale quantum devices. To accelerate the Monte Carlo sampling process in VQS-QJ-LTLME, we introduce an efficient sampling method, named No-evolution sampling (NES). The VQS-QJ-LTLME aided by NES requires simulating only n3 + 1 trajectories on quantum computers, and then makes 106 to 107 samplings on classical computers in a few seconds. To demonstrate the performance of the VQS-QJ-LTLME algorithm, we simulate the dynamics of a two-level spin-boson model and a four-level reduced Fenna-Matthews-Olson system with real superconducting quantum computers and classical simulators. It is shown that the simulations produced by VQS-QJ-LTLME algorithm align closely with those obtained from the purely classical methods.

The Control Policy &lt;i&gt;M/M/c/N&lt;/i&gt; Interrelated Queue with Manageable Incoming Rates, Reverse Balking and Impatient Customers

This study explores an interconnected M/M/c/N queueing model that incorporates reverse balking, reneging, a control technique, and adjustable arrival rates. In reverse balking, the likelihood of a visitor deciding to join or leave a queue is influenced by the current system size, with a higher probability of joining as the system size grows. Conversely, long wait times can lead to customer impatience, causing them to leave the queue before receiving service (reneging). Service begins with the arrival of the initial customer (TL) and continues until the system is empty. We are developing a multi-server queueing system with adjustable arrival rates that includes reverse balking and considers impatient customers. For this model, we determine the steady-state condition and performance metrics such as average waiting time and average system size.