Reinforcement Learning reveals fundamental limits on the mixing of active particles

The control of far-from-equilibrium physical systems, including active materials, requires advanced control strategies due to the non-linear dynamics and long-range interactions between particles, preventing explicit solutions to optimal control problems....

Fisher Identifiability Analysis of Longitudinal Vehicle Dynamics

This paper investigates the theoretical Cram´er-Rao bounds on estimation accuracy of longitudinal vehicle dynamics parameters. This analysis is motivated by the value of parameter estimation in various applications, including chassis model validation and active safety. Relevant literature addresses this demand through algorithms capable of estimating chassis parameters for diverse conditions. While the implementation of such algorithms has been studied, the question of fundamental limits on their accuracy remains largely unexplored. We address this question by presenting two contributions. First, this paper presents theoretical findings which reveal the prevailing effects underpinning vehicle chassis parameter identifiability. We then validate these findings with data from on-road experiments. Our results demonstrate, among a variety of effects, the strong relevance of road grade variability in determining parameter identifiability from a drive cycle. These findings can motivate improved experimental designs in the future.

PHYSICS OF MOSFET NANOTRANSISTORS: FUNDAMENTAL LIMITS AND RESTRICTIONS

In the last one from the series of the tutorial review articles, devoted to physics of modern nanotransistors and aimed to serve reseachers, ingeneers, students and teachers in the universities, it is demonstrated that the existence of the minimal energy for recording of 1 bite of information leads to fundamental restriction on minimal MOSFET channel length and on minimal time of transistor swithching. The obtained simple estimation Lmin = 1.2 nm (for room temperature) is somewhat lower, than in reality, and it looks like that Si FETs with a channel shorter than 2.5–3 nm would newer be fabricated. This correlates with the results of numerical modeling of electron transport through the channel, which demonstrate that for short channels the greater part of current passes by tunneling below the barrier top, and the transistor loses its functionality, because the current in source-drain circuit is no longer governed by gate voltage.

How organisms come to know the world: fundamental limits on artificial general intelligence

Artificial intelligence has made tremendous advances since its inception about seventy years ago. Self-driving cars, programs beating experts at complex games, and smart robots capable of assisting people that need care are just some among the successful examples of machine intelligence. This kind of progress might entice us to envision a society populated by autonomous robots capable of performing the same tasks humans do in the near future. This prospect seems limited only by the power and complexity of current computational devices, which is improving fast. However, there are several significant obstacles on this path. General intelligence involves situational reasoning, taking perspectives, choosing goals, and an ability to deal with ambiguous information. We observe that all of these characteristics are connected to the ability of identifying and exploiting new affordances—opportunities (or impediments) on the path of an agent to achieve its goals. A general example of an affordance is the use of an object in the hands of an agent. We show that it is impossible to predefine a list of such uses. Therefore, they cannot be treated algorithmically. This means that “AI agents” and organisms differ in their ability to leverage new affordances. Only organisms can do this. This implies that true AGI is not achievable in the current algorithmic frame of AI research. It also has important consequences for the theory of evolution. We argue that organismic agency is strictly required for truly open-ended evolution through radical emergence. We discuss the diverse ramifications of this argument, not only in AI research and evolution, but also for the philosophy of science.

Fundamental Limits on the Uplink Performance of the Dynamic-Ordered Successive Interference Cancellation Receiver

<div>This work puts forth a novel analytical approach to evaluate the performance that power-domain Non-Orthogonal Multiple Access (NOMA) achieves on the uplink of a single cell. A dynamic-ordered Successive Interference Cancellation (SIC) receiver is considered, and both the case of Rayleigh and lognormal-shadowed Rayleigh fading are examined. System performance is assessed analytically, deriving either exact or approximated closed-form expressions, whose correctness and excellent accuracy are validated through Monte Carlo simulations. The analysis discloses the effects on performance of an arbitrary number n of simultaneously transmitting users, therefore unveiling where the insourmountable limits of the dynamic-ordered SIC receiver lie. Moreover, the proposed methodology allows to quantify</div><div>the impact of lognormal shadowing on NOMA efficacy. </div>

Fundamental Limits on the Uplink Performance of the Dynamic-Ordered Successive Interference Cancellation Receiver

<div>This work puts forth a novel analytical approach to evaluate the performance that power-domain Non-Orthogonal Multiple Access (NOMA) achieves on the uplink of a single cell. A dynamic-ordered Successive Interference Cancellation (SIC) receiver is considered, and both the case of Rayleigh and lognormal-shadowed Rayleigh fading are examined. System performance is assessed analytically, deriving either exact or approximated closed-form expressions, whose correctness and excellent accuracy are validated through Monte Carlo simulations. The analysis discloses the effects on performance of an arbitrary number n of simultaneously transmitting users, therefore unveiling where the insourmountable limits of the dynamic-ordered SIC receiver lie. Moreover, the proposed methodology allows to quantify</div><div>the impact of lognormal shadowing on NOMA efficacy. </div>

Fundamental limits of high-efficiency silicon and compound semiconductor power amplifiers in 100-300 GHz bands

This paper reviews the requirements for future digital arrays in terms of power amplifier requirements for output power and efficiency and the device technologies that will realize future energy-efficient communication and sensing electronics for the upper millimeter-wave bands (100-300 GHz). Fundamental device technologies are reviewed to compare the needs for compound semiconductors and silicon processes. Power amplifier circuit design above 100 GHz is reviewed based on load line and matching element losses. We present recently presented class-A and class-B PAs based on a InP HBT process that have demonstrated record efficiency and power around 140 GHz while discussing circuit techniques that can be applied in a variety of integrated circuits.

Fundamental limits and optimal estimation of the resonance frequency of a linear harmonic oscillator

All physical oscillators are subject to thermodynamic and quantum perturbations, fundamentally limiting measurement of their resonance frequency. Analyses assuming specific ways of estimating frequency can underestimate the available precision and overlook unconventional measurement regimes. Here we derive a general, estimation-method-independent Cramer Rao lower bound for a linear harmonic oscillator resonance frequency measurement uncertainty, seamlessly accounting for the quantum, thermodynamic and instrumental limitations, including Fisher information from quantum backaction- and thermodynamically driven fluctuations. We provide a universal and practical maximum-likelihood frequency estimator reaching the predicted limits in all regimes, and experimentally validate it on a thermodynamically limited nanomechanical oscillator. Low relative frequency uncertainty is obtained for both very high bandwidth measurements (≈10−5 for τ = 30 μs) and measurements using thermal fluctuations alone (<10−6). Beyond nanomechanics, these results advance frequency-based metrology across physical domains.