Fundamental Limits Research Articles

Discharge mitigation methods in MPGD-based detectors

This work reviews various methods used to minimize the probability of discharge occurrence in MPGDs or to mitigate the effect of spark discharges on the detector system. These include techniques that can reduce the probability that the fundamental discharge limits of MPGD structures are reached during detector operation, methods based on the HV scheme optimization, or the implementation of resistive electrodes to enhance local discharge quenching capabilities in an amplification structure. In addition, design optimization and quality control methods to ensure stable, long-term operation of an MPGD-based detector, are considered.

Disney Princess Movies' Development and Dilemmas From a Feminist Perspective

The purpose of this study is to critically analyze the image of Disney princesses using a feminist perspective. The study aims to explore the positive and negative impacts of the image of princesses and how it has influenced film making as social mores have changed and women's liberation has been promoted. The study explores the ways in which women have been portrayed throughout history through exhaustive case studies, demonstrating how princesses have changed in response to the times in which they have been portrayed. This study recognizes that while significant progress has been made in portraying princesses as more autonomous and powerful, prejudices and fundamental limitations remain. By examining these issues, this study seeks to reveal that the image of the princess still needs to be improved to better align with modern feminist values. It also calls on Disney to be brave enough to break out of the current image of princesses as well as the storytelling framework, and to explore more possibilities in female characters

Low‐Temperature Epitaxy of Perovskite WO3 Thin Films under Atmospheric Conditions

As Si electronics hits fundamental performance limits, oxide integration emerges as a solution to augment the next generation of electronic and optical devices. Specifically, oxide perovskites provide diverse functionalities with a potential to create, tune, and combine emergent phenomena at interfaces. High‐level crystalline order is needed to realize these functionalities, often achieved through epitaxy. However, large‐scale implementation in consumer devices faces challenges due to the need for high‐temperature deposition in complex vacuum systems. Herein, this challenge is addressed using atmospheric pressure spatial chemical vapor deposition, a thin‐film fabrication technique that can rapidly produce uniform films at sub‐400 °C temperatures under atmospheric conditions over ≈cm2 areas. Thus, the deposition of epitaxial perovskite tungsten trioxide, WO3, thin films is demonstrated at a rate of 5 nm min−2 on single‐crystal substrates at 350 °C in open‐air conditions enabling a high‐throughput process. The resulting films exhibit crystallographic and electronic properties comparable to vacuum‐based growth above 500 °C. The high‐quality epitaxy is attributed to the energetics of the exothermic decomposition reaction of the W[CO]6 precursors combined with the stabilization of a hot zone near the substrate surface. From this work, the way can be paved for low‐temperature atmospheric‐pressure epitaxy of a wide range of other perovskite thin films.

Rate-Distortion-Perception Optimized Neural Speech Transmission System for High-Fidelity Semantic Communications.

We consider the problem of learned speech transmission. Existing methods have exploited joint source-channel coding (JSCC) to encode speech directly to transmitted symbols to improve the robustness over noisy channels. However, the fundamental limit of these methods is the failure of identification of content diversity across speech frames, leading to inefficient transmission. In this paper, we propose a novel neural speech transmission framework named NST. It can be optimized for superior rate-distortion-perception (RDP) performance toward the goal of high-fidelity semantic communication. Particularly, a learned entropy model assesses latent speech features to quantify the semantic content complexity, which facilitates the adaptive transmission rate allocation. NST enables a seamless integration of the source content with channel state information through variable-length joint source-channel coding, which maximizes the coding gain. Furthermore, we present a streaming variant of NST, which adopts causal coding based on sliding windows. Experimental results verify that NST outperforms existing speech transmission methods including separation-based and JSCC solutions in terms of RDP performance. Streaming NST achieves low-latency transmission with a slight quality degradation, which is tailored for real-time speech communication.

Detector size selection for long-range targeting performance in the extended shortwave infrared band

Interest in the eSWIR band is growing due to focal plane array technology advancements with mercury cadmium telluride and type-II superlattice materials. As design and fabrication processes improve, eSWIR detector size, weight, and power can now be optimized. For some applications, it is desirable to have a smaller detector size. Reduced solar illumination in the 2 to 2.5 μm spectral range creates a fundamental limit to passive imaging performance in the eSWIR band where the resolution benefit of small detectors cannot out-compete the reduced SNR in photon-starved environments. This research explores the underlying theory using signal-to-noise ratio radiometry and modeled target discrimination performance to assess the optimal detector size for eSWIR dependent upon illumination conditions. Finally, we model continuous-wave laser illumination in the eSWIR band to compare the effect of detector size on active and passive imaging for long-range object discrimination.

An Overview of Privacy-Enhancing Technologies in Biometric Recognition

Privacy-enhancing technologies are technologies that implement fundamental data protection principles. With respect to biometric recognition, different types of privacy-enhancing technologies have been introduced for protecting stored biometric data which are generally classified as sensitive. In this regard, various taxonomies and conceptual categorizations have been proposed and standardisation activities have been carried out. However, these efforts have mainly been devoted to certain sub-categories of privacy-enhancing technologies and therefore lack generalization. This work provides an overview of concepts of privacy-enhancing technologies for biometric recognition in a unified framework. Key properties and differences between existing concepts are highlighted in detail at each processing step. Fundamental characteristics and limitations of existing technologies are discussed and related to data protection techniques and principles. Moreover, scenarios and methods for the assessment of privacy-enhancing technologies for biometric recognition are presented. This paper is meant as a point of entry to the field of data protection for biometric recognition applications and is directed towards experienced researchers as well as non-experts.

Spatial circulatory networks based on the peripheral medial axis transform

This article presents a method for constructing circulatory networks that intrinsically combine geometric, topological, and semantic spatial attributes. The objective of this work is to generate concise graph representations extracted from spatial geometry that may be used for wayfinding and code compliance analyses to inform architectural design and urban planning. Our approach is based on shape analysis using the Medial Axis Transform skeletonization method. We present a process for the semantic classification of its nodes and edges by constructing an analytical rational piece-wise 3D surface representation. This overcomes the problem of identifying salient or otherwise graph features. Furthermore, we augment the networks with peripheral pathways. This addresses the fundamental limitation of skeletal graphs forcing paths exclusively through the middle of space and thus producing unreasonable detours. We demonstrate that our approach encompasses subtle circulatory features and generates concise graphs for open and free-form spaces that do not exhibit corridor-like structures.

An information theoretic metric for measurement vulnerability to data integrity attacks on smart grids

AbstractA novel metric that describes the vulnerability of the measurements in power systems to data integrity attacks is proposed. The new metric, coined vulnerability index (VuIx), leverages information theoretic measures to assess the attack effect in terms of the fundamental limits of the disruption and detection tradeoff. The result of computing the VuIx of the measurements in the system yields an ordering of their vulnerability based on the degree of exposure to data integrity attacks. This new framework is used to assess the measurement vulnerability of IEEE 9‐bus and 30‐bus test systems and it is observed that power injection measurements are significantly more vulnerable to data integrity attacks than power flow measurements. A detailed numerical evaluation of the VuIx values for IEEE test systems is provided.

Fluorescence amplification in laser-pumped random media: Fundamental limitations

Experimental data on the narrowing of fluorescence spectra of laser-pumped random media are interpreted within the framework of a probabilistic model of incoherent amplification of the stimulated component of fluorescence. R6G- and DCM-doped layers of dense-packed anatase and anatase-rutile particles and suspensions of DCM crystallites were examined under pulse-periodic laser pumping with various pump intensities at the wavelength of 532 nm. It was shown that, in the case of quasi-stationary fluorescence response at high pump intensities, amplification of stochastically propagating partial components of fluorescence field at various wavelengths is governed by the pump-independent factor of fluorescence amplification and the average number of stimulated emission acts in the pumped system. Analysis of the experimental data has shown that, despite certain simplifying assumptions, the considered model reasonably describes evolution of the fluorescence spectra of random fluorescent media with the increase in the pump intensity. A procedure of recovery of the fluorescence amplification factor from the sets of fluorescence spectra obtained at various pump intensities is considered. Features of the spectral shapes of the recovered amplification factors caused by the influence of the scattering matrices in pumped media are discussed.

What Formal Languages Can Transformers Express? A Survey

Abstract As transformers have gained prominence in natural language processing, some researchers have investigated theoretically what problems they can and cannot solve, by treating problems as formal languages. Exploring such questions can help clarify the power of transformers relative to other models of computation, their fundamental capabilities and limits, and the impact of architectural choices. Work in this subarea has made considerable progress in recent years. Here, we undertake a comprehensive survey of this work, documenting the diverse assumptions that underlie different results and providing a unified framework for harmonizing seemingly contradictory findings.

Wideband-tunable microwave photonic filter using dissipative self-interference microring resonators

We propose and demonstrate a widely tunable microwave photonic filter with controlled frequency agility, bandwidth reconfigurability and flexible switching functions. It is based on the self-interference microring aided by an asymmetric Mach–Zehnder interferometer, breaking the fundamental microring footprint limit and achieving a doubled free spectral range (123.2 GHz) with a strong out-of-band rejection. Simulation results show that a bandpass microwave photonic filter can be tuned across a 60 GHz frequency range with a varied 3-dB bandwidth from 2.13 GHz to 40.7 GHz in a cascaded dual-ring topology. Its RF out-of-band rejection ratio is improved by more than 60 dB in the high frequency region due to a perfect residual phase cancellation. A dual-band notch microwave photonic filter with an extinction ratio of about 50 dB and a frequency tunable range of about 27.7 GHz is also demonstrated, showing its broadly applicability. Our method highlights its suitability to improve chip-scale wideband and high-performance RF receiver systems.

Speckle-enabled in vivo demixing of neural activity in the mouse brain.

Functional imaging of neuronal activity in awake animals, using a combination of fluorescent reporters of neuronal activity and various types of microscopy modalities, has become an indispensable tool in neuroscience. While various imaging modalities based on one-photon (1P) excitation and parallel (camera-based) acquisition have been successfully used for imaging more transparent samples, when imaging mammalian brain tissue, due to their scattering properties, two-photon (2P) microscopy systems are necessary. In 2P microscopy, the longer excitation wavelengths reduce the amount of scattering while the diffraction-limited 3D localization of excitation largely eliminates out-of-focus fluorescence. However, this comes at the cost of time-consuming serial scanning of the excitation spot and more complex and expensive instrumentation. Thus, functional 1P imaging modalities that can be used beyond the most transparent specimen are highly desirable. Here, we transform light scattering from an obstacle into a tool. We use speckles with their unique patterns and contrast, formed when fluorescence from individual neurons propagates through rodent cortical tissue, to encode neuronal activity. Spatiotemporal demixing of these patterns then enables functional recording of neuronal activity from a group of discriminable sources. For the first time, we provide an experimental, in vivo characterization of speckle generation, speckle imaging and speckle-assisted demixing of neuronal activity signals in the scattering mammalian brain tissue. We found that despite an initial fast speckle decorrelation, substantial correlation was maintained over minute-long timescales that contributed to our ability to demix temporal activity traces in the mouse brain in vivo. Informed by in vivo quantifications of speckle patterns from single and multiple neurons excited using 2P scanning excitation, we recorded and demixed activity from several sources excited using 1P oblique illumination. In our proof-of-principle experiments, we demonstrate in vivo speckle-assisted demixing of functional signals from groups of sources in a depth range of 220-320 µm in mouse cortex, limited by available speckle contrast. Our results serve as a basis for designing an in vivo functional speckle imaging modality and for maximizing the key resource in any such modality, the speckle contrast. We anticipate that our results will provide critical quantitative guidance to the community for designing techniques that overcome light scattering as a fundamental limitation in bioimaging.

Atomic physics on a 50-nm scale: Realization of a bilayer system of dipolar atoms.

Controlling ultracold atoms with laser light has greatly advanced quantum science. The wavelength of light sets a typical length scale for most experiments to the order of 500 nanometers (nm) or greater. In this work, we implemented a super-resolution technique that localizes and arranges atoms on a sub-50-nm scale, without any fundamental limit in resolution. We demonstrate this technique by creating a bilayer of dysprosium atoms and observing dipolar interactions between two physically separated layers through interlayer sympathetic cooling and coupled collective excitations. At 50-nm distance, dipolar interactions are 1000 times stronger than at 500 nm. For two atoms in optical tweezers, this should enable purely magnetic dipolar gates with kilohertz speed.

Preserving Mesoporosity in Type III Porous Liquids through Dual-layer Surface Weaving.

The fundamental limitation for pore preservation in a Type III porous liquid (T3PL) is the need for a small aperture from the porous filler to realize size exclusion of a bulky solvent. We present a dual-layer surface weaving strategy that can disregard this limitation and achieve micro- and mesoporous metal-organic framework (MOF)-based T3PLs even with apertures much larger than the solvent molecules. By first weaving a tight network of poly(tert-butyl methacrylate) on the MOF surface, the poly(dimethylsiloxane) (PDMS) solvent can be effectively excluded from the pores while smaller guest molecules such as CO2, C2H4, and H2O can freely access the interior, as confirmed by low-pressure adsorption isotherms. Further application of a PDMS-containing polymer coating helps lower the viscosity of the PL due to increased particle dispersibility. This strategy has resulted in the successful construction of T3PLs with aperture sizes up to 3.1 nm.

Preserving Mesoporosity in Type III Porous Liquids through Dual‐layer Surface Weaving

AbstractThe fundamental limitation for pore preservation in a Type III porous liquid (T3PL) is the need for a small aperture from the porous filler to realize size exclusion of a bulky solvent. We present a dual‐layer surface weaving strategy that can disregard this limitation and achieve micro‐ and mesoporous metal–organic framework (MOF)‐based T3PLs even with apertures much larger than the solvent molecules. By first weaving a tight network of poly(tert‐butyl methacrylate) on the MOF surface, the poly(dimethylsiloxane) (PDMS) solvent can be effectively excluded from the pores while smaller guest molecules such as CO2, C2H4, and H2O can freely access the interior, as confirmed by low‐pressure adsorption isotherms. Further application of a PDMS‐containing polymer coating helps lower the viscosity of the PL due to increased particle dispersibility. This strategy has resulted in the successful construction of T3PLs with aperture sizes up to 3.1 nm.

ParallEdge: Exploiting Computing-Mobility Parallelism for Efficient 5G/6G Edge Computing

With the emergence of the 5G/6G communications, edge computing has attracted increasing research interests in recent years. To provide pervasive 5G/6G edge computing services, numerous edge servers are required for service coverage, and the deployment cost can be <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\gt$</tex-math></inline-formula> 10000 times larger than the deployment cost of the 4G infrastructure. To address this fundamental limit, we propose ParallEdge, a deployment scheme that employs mobile edge servers for cost-effective service coverage. ParallEdge is designed based on the observation that the processing delay and server moving delay become comparable in many computing-intensive applications in the 5G/6G edge computing. Unlike the traditional “move-then-process” frameworks, ParallEdge follows a “move-while-processing” paradigm, which exploits the parallelism between task processing and server movement to enable resource sharing among more users. Moreover, with the joint optimization of path planning and task scheduling for multiple mobile servers, the deployment cost for service coverage can be further reduced. We analyze the approximation gap of the proposed algorithm, and conduct extensive simulation experiments based on the real-world application data, and the results show that ParallEdge can significantly reduce deployment cost and improve resource utilization compared to the state-of-the-art schemes.

Poling-free relaxor-PbTiO3 single crystals

Relaxor-PbTiO3 ferroelectric single crystals have drawn attention aiming at high-end piezoelectric applications thanks to their excellent piezoelectric properties. Like all the other ferroelectrics, relaxor-PbTiO3 single crystals can only be piezoelectrically active upon being electrically poled. However, this poled state is thermally unstable, limiting their uses because of their relatively low depolarization temperature. Here, we show that a non-destructible permanent poled state can be realized in relaxor-PbTiO3 single crystals by forming a 0–3 composite in the presence of charged mobile point defects. We demonstrate this on solid-state grown 0.71Pb(Mg1/3Nb2/3)O3-0.29PbTiO3 single crystals doped with Mn (Mn-PMNT) as a donor with well-aligned and dispersed boron-rich MgO-based inclusions (MBIs). Mn-PMNTMBI sharing [001] axis with arrayed MBIs were spontaneously polarized during cooling across the Curie temperature without an external electric field. The piezoelectric coefficient and dielectric permittivity of self-poled Mn-PMNTMBI crystals were as large as 90 % of that achieved by a direct-current poling treatment at room temperature, and such poled state was reproducible against repeated thermal cycles. We expect that the poling-free high-performance piezoelectric relaxor-PbTiO3 single crystals offer an avenue for piezoelectric-based devices by removing the working temperature limit as one of the inherent fundamental limitations.

Room-temperature low-threshold avalanche effect in stepwise van-der-Waals homojunction photodiodes

Avalanche or carrier-multiplication effect, based on impact ionization processes in semiconductors, has a great potential for enhancing the performance of photodetector and solar cells. However, in practical applications, it suffers from high threshold energy, reducing the advantages of carrier multiplication. Here, we report on a low-threshold avalanche effect in a stepwise WSe2 structure, in which the combination of weak electron-phonon scattering and high electric fields leads to a low-loss carrier acceleration and multiplication. Owing to this effect, the room-temperature threshold energy approaches the fundamental limit, Ethre ≈ Eg, where Eg is the bandgap of the semiconductor. Our findings offer an alternative perspective on the design and fabrication of future avalanche and hot-carrier photovoltaic devices.

Visual control for robotic 3D printing on a moving platform

In recent years, there has been significant progress in developing specialized 3D printing techniques that cater to various demanding applications. However, the current state of this technology is challenged when it comes to complex in situ printing scenarios, which require a controlled printing platform. The lack of a stable printing platform is a fundamental limitation of its use in in situ applications. To address this issue, we present a novel platform-independent 3D fabrication process that enables printing on platforms with non-cooperative movement. The process overcomes the challenge of high-speed tracking, motion compensation, and real-time printing by developing a closed-loop visual feedback-controlled robotic printing process. The proposed process incorporates a marker-based visual detection and tracking controller setup, which is discussed in detail. The algorithm consists of two loops running asynchronously: a high-speed inner control loop and an outer measurement loop. This setup enables precise and accurate tracking of the printing platform, compensating for any disturbances during the printing process. Our experimental results demonstrate the successful printing of simple linear geometries, even with low-disturbing platform velocities. Moreover, the tracking controllers' ability to handle measurement occlusion is validated, showing the proposed process's robustness and effectiveness. Our work provides a significant step towards enabling 3D printing in complex in situ printing scenarios.

Overcoming limitations in current measures of drug response may enable AI-driven precision oncology

Machine learning (ML) models of drug sensitivity prediction are becoming increasingly popular in precision oncology. Here, we identify a fundamental limitation in standard measures of drug sensitivity that hinders the development of personalized prediction models – they focus on absolute effects but do not capture relative differences between cancer subtypes. Our work suggests that using z-scored drug response measures mitigates these limitations and leads to meaningful predictions, opening the door for sophisticated ML precision oncology models.