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At least 199 records · Page 11

Learnability Transitions in Monitored Quantum Dynamics via Eavesdropper’s Classical Shadows

Monitored quantum dynamics—unitary evolution interspersed with measurements—has recently emerged as a rich domain for phase structure in quantum many-body systems away from equilibrium. Here we study monitored dynamics from the point of view of an eavesdropper who has access to the classical measurement outcomes, but not to the quantum many-body system. We show that a measure of information flow from the quantum system to the classical measurement record—the —undergoes a phase transition in correspondence with the measurement-induced phase transition (MIPT). This transition determines the eavesdropper’s (in)ability to learn properties of an unknown initial quantum state of the system, given a complete classical description of the monitored dynamics and arbitrary classical computational resources. We make this learnability transition concrete by defining classical shadow protocols that the eavesdropper may apply to this problem, and show that the MIPT manifests as a transition in the sample complexity of various shadow-estimation tasks, which become harder in the low-measurement phase. We focus on three applications of interest: Pauli expectation values (where we find the MIPT appears as a point of optimal learnability for typical Pauli operators), many-body fidelity, and global charge in U ( 1 ) -symmetric dynamics. Our work unifies different manifestations of the MIPT under the umbrella of and gives this notion a general operational meaning via classical shadows. Published by the American Physical Society 2024

Physics↗

Conjoint-measurement framework for the study of probabilistic information processing.

The theory of conjoint measurement described by Krantz et al. (1971) is shown to indicate how a descriptive model of human processing of probabilistic information built around Bayes' rule is to be tested and how it is to be used to obtain subjective scale values. Specific relationships concerning these scale values are shown to emerge, and the theoretical prospects resulting from this development are discussed.

Wallsten, T. S.↗

The Generalization of Mutual Information as the Information between a Set of Variables: The Information Correlation Function Hierarchy and the Information Structure of Multi-Agent Systems

The topic of this paper is a hierarchy of information-like functions, here named the information correlation functions, where each function of the hierarchy may be thought of as the information between the variables it depends upon. The information correlation functions are particularly suited to the description of the emergence of complex behaviors due to many- body or many-agent processes. They are particularly well suited to the quantification of the decomposition of the information carried among a set of variables or agents, and its subsets. In more graphical language, they provide the information theoretic basis for understanding the synergistic and non-synergistic components of a system, and as such should serve as a forceful toolkit for the analysis of the complexity structure of complex many agent systems. The information correlation functions are the natural generalization to an arbitrary number of sets of variables of the sequence starting with the entropy function (one set of variables) and the mutual information function (two sets). We start by describing the traditional measures of information (entropy) and mutual information.

Wolf, David R.↗

Model certainty in cellular network-driven processes with missing data

Mathematical models are often used to explore network-driven cellular processes from a systems perspective. However, a dearth of quantitative data suitable for model calibration leads to models with parameter unidentifiability and questionable predictive power. Here we introduce a combined Bayesian and Machine Learning Measurement Model approach to explore how quantitative and non-quantitative data constrain models of apoptosis execution within a missing data context. We find model prediction accuracy and certainty strongly depend on rigorous data-driven formulations of the measurement, and the size and make-up of the datasets. For instance, two orders of magnitude more ordinal (e.g., immunoblot) data are necessary to achieve accuracy comparable to quantitative (e.g., fluorescence) data for calibration of an apoptosis execution model. Notably, ordinal and nominal (e.g., cell fate observations) non-quantitative data synergize to reduce model uncertainty and improve accuracy. Finally, we demonstrate the potential of a data-driven Measurement Model approach to identify model features that could lead to informative experimental measurements and improve model predictive power.

59 BASIC BIOLOGICAL SCIENCES↗

A Simulation Model for Studying Effects of Pollution and Freshwater Inflow on Secondary Productivity in an Ecosystem

A mathematical model of an ecosystem is developed. Secondary productivity is evaluated in terms of man related and controllable factors. Information from an existing physical parameters model is used as well as pertinent biological measurements. Predictive information of value to estuarine management is presented. Biological, chemical, and physical parameters measured in order to develop models of ecosystems are identified.

Johnson, R. W.↗

Measurement of operator workload in an information processing task

This was an experimental study to develop an improved methodology for measuring workload in an information processing task and to assess the effects of shift length and communication density (rate of information flow) on the ability to process and classify verbal messages. Each of twelve subjects was exposed to combinations of three shift lengths and two communication densities in a counterbalanced, repeated measurements experimental design. Results indicated no systematic variation in task performance measures or in other dependent measures as a function of shift length or communication density. This is attributed to the absence of a secondary loading task, an insufficiently taxing work schedule, and the lack of psychological stress. Subjective magnitude estimates of workload showed fatigue (and to a lesser degree, tension) to be a power function of shift length. Estimates of task difficulty and fatigue were initially lower but increased more sharply over time under low density than under high density conditions. An interpretation of findings and recommedations for furture research are included. This research has major implications to human workload problems in information processing of air traffic control verbal data.

Jenney, L. L.↗

Adaptive Multi-Sensor Localization Information Fusion for Autonomous Urban Air Mobility Operations

An adaptive method is developed to iteratively fuse the information provided by multiple sensors to enable autonomous urban air mobility type operations. First, noisy and bias corrupted IMU readings are processed as soon as they arrive using kinematic equations represented in the vehicle's body frame. To correct the systems drift resulting from the integration, an information content measure is introduced to decide on the environment. For the cluttered environment the information provided by environmental sensors is counted as reliable and the drift correction as accurate. For the open space, the GPS data is counted as reliable, and the drift correction is done based on the GPS readings. The measurement noise effects are minimize using Iterated Extended Kalman Filter framework. The algorithm is implemented in the in-house developed FlightDeckz simulation environment using an IMU model, simulated video recorded from a camera mounted on the vehicle (for the purpose of this study, outside scenery was generated with XPlane), which flies in an urban environment, and GPS data generated from the environment's digital map.

Onboard Perception↗

Exploring Hydrologic Model Process Connectivity at the Continental Scale Through an Information Theory Approach

Exploring water fluxes between hydrological model (HM) components is essential to assess and improve model realism. Many classical metrics for HM diagnosis rely solely on streamflow and hence provide limited insights into model performance across processes. This study applies an information theory measure known as “transfer entropy” (TE) to systematically quantify the transfer of information among major HM components. To test and demonstrate the benefits of TE, we use the Framework for Understanding Structural Errors (FUSE) model to mimic and compare four commonly used HM structures, VIC, PRMS, SACRAMENTO, and TOPMODEL, across 671 catchments spanning a variety of hydrologic regimes in the conterminous United States. We explore connections between HM components and catchment landscape characteristics (e.g., climate, topography, soil, and vegetation) and characterize their nonlinear associations using distance correlation and Spearman correlation coefficients. Our results indicate that while the information transferred from precipitation to runoff is similar across model structures (likely as a result of calibration), the information transferred among other components can vary significantly from a FUSE structure to another. We find that aridity, precipitation duration and frequency, snow fraction, mean elevation, forest area, and leaf area index are often significantly associated with TE between the main HM components. Here, we propose that the presence of meaningful nonlinear associations can be used to diagnose process representation in HMs. Our results highlight the necessity to enhance the conventional streamflow-only calibration approach for a more realistic representation of water dynamics in the models.

large-sample hydrology↗

Sister Rod Destructive Examinations (FY2021) Appendix G: CRIFT Uncertainty Calculations

This document discusses the uncertainty of measurements associated with the CIRFT system and the resulting uncertainty in the acquired measurements and calculated information. The primary parameters measured during the CIRFT test include the deflection magnitude of the specimen, the load applied in bending, and the number of cycles to specimen gross failure. The associated primary calculated parameters are the bending radius/curvature and bending moment. Secondary calculated parameters include specimen stress and strain amplitudes and flexural rigidity. The uncertainty associated with the primary and secondary calculated parameters are investigated based on the known uncertainty in the measured parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Sister Rod Destructive Examinations (FY23) Appendix G: CIRFT Uncertainty Calculations

This document discusses the uncertainty of measurements associated with the cyclic integrated reversible-bending fatigue tester (CIRFT) system and the resulting uncertainty in the acquired measurements and calculated information. The primary parameters measured during the CIRFT test include the deflection magnitude of the specimen, the load applied during bending, and the number of cycles to specimen gross failure. The associated primary calculated parameters are the bending radius/curvature and the bending moment. Secondary calculated parameters include specimen stress and strain amplitudes, as well as flexural rigidity. The uncertainty associated with the primary and secondary calculated parameters is investigated based on the known uncertainty in the measured parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Sister Rod Destructive Examinations (FY23): Appendix H: Instron Uncertainty Calculations

This document discusses the uncertainty of measurements associated with the Instron system and the resulting uncertainty in the acquired measurements and calculated information. The primary parameters measured during the Instron test include the applied load and specimen deflection. The associated primary calculated parameters are the maximum beam deflection at the rod’s axial center and modulus of elasticity. Secondary calculated parameters include specimen stress and strain amplitudes, as well as flexural rigidity. The uncertainty associated with the primary and secondary calculated parameters was investigated based on the known uncertainty in the measured parameters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Cloud microstructure as determined by an optical cloud particle spectrometer.

Use of an improved single-particle light-scattering instrument for measurement of cloud microstructure in field studies. Cloud particle size and number information is measured over 12 sizing intervals, in the range from 4 to 85 microns in diameter. The microstructure can be observed in real time and with a spatial resolution not previously reported. The general features of water cloud droplet size and number distributions are consistent with previous direct capture and replication studies. The transition from water to ice phase regions in cumuliform clouds can be inferred from dramatic changes observed in the distribution features. Results are also presented for stratus and cirrus cloud penetrations.

Ryan, R. T.↗

Application of Bayesian decision theory to airborne gamma snow measurement

Measured values of several variables are incorporated into the calculation of snow water equivalent as measured from an aircraft by snow attenuation of terrestrial gamma radiation. Bayesian decision theory provides a snow water equivalent measurement by taking into account the uncertainties in the individual measurement variables and filtering information about the measurement variables through prior notions of what the calculated variable (water equivalent) should be.

Bissell, V. C.↗

Acoustic Wave Propagation in Pressure Sense Lines

Sense lines are used in pressure measurements to passively transmit information from hostile environments to areas where transducers can be used. The transfer function of a sense line can be used to obtain information about the measured environment from the protected sensor. Several properties of this transfer function are examined, including frequency dependence, Helmholtz resonance, and time of flight delay.

Vitarius, Patrick↗

Lunar Water ISRU Measurement Study (LWIMS): Establishing a Measurement Plan for Identification and Characterization of a Water Reserve

NASA’s Artemis program aims to achieve a sustainable lunar presence by 2028. To carry out sustained crewed surface operations, In-Situ Resource Utilization (ISRU), which would use lunar resources (e.g., water) to produce mission consumables, will be critical. Water-bearing materials have been identified at both lunar poles, butthe nature and extent of this resource is not well understood. Identification of the presence of water alone is not adequate for ISRU architecture planning and engineering design. The Lunar Water ISRU Measurement Study (LWIMS) assessed and defined the type, amount, and fidelity of the information and measurements needed to select mining locations for lunar water ISRU and to define requirements for ISRU hardware and architecture development. Current ISRU requirements were used to define a water ‘reserve’ in this context. A measurement plan to achieve these goals includes three key elements; a predictive ‘water favorability’ model to identify and map potential deposits, continued assessment of orbital data, and three types of landed missions to make direct ground measurements. Corresponding mission scenarios and instrument suites will depend on risk posture and timelines for ISRU implementation.

In situ resource utilization↗

Photogrammetry: Develop methods for detecting deviations from expected geometry of components in a glovebox environment (Lawrence Livermore National Laboratory Aging and Lifetimes Program FY23, Milestone 8651, Grading Criterion #4)

Measurements in glovebox environments are challenging to conduct. Currently deployed techniques are time consuming and provide limited information. These limitations make current disposition and future assessments of products challenging. In FY23 we developed methods for detecting deviations of components in a glovebox environment that address these shortcomings by rapidly collecting information-dense measurements. Conducted tests demonstrate that camera pose (position and orientation) can be derived for images utilized in the photogrammetry process. This information, in conjunction with common image processing techniques, enables automated detection and size estimation of surface features. First, image processing is used to identify marks, or localized regions, that standout from the surrounding area. Then, the physical size of the region can be estimated because scale can be determined for photogrammetry images. Development of this methods shows that photogrammetry can identify measurable deviations from expected geometries. Although measurement error when using this technique through a glovebox window still needs to be reduced, this capability shows promise for eliminating or reducing the use of tedious manual measurements.

42 ENGINEERING↗

An information theory approach for evaluating earth radiation budget (ERB) measurements - Nonuniform sampling of reflected shortwave radiation

An information theory approach to examine the temporal nonuniform sampling characteristics of shortwave (SW) flux for earth radiation budget (ERB) measurements is suggested. The information gain is computed by computing the information content before and after the measurements. A stochastic diurnal model for the SW flux is developed, and measurements for different orbital parameters are examined. The methodology is applied to specific NASA Polar platform and Tropical Rainfall Measuring Mission (TRMM) orbital parameters. The information theory approach, coupled with the developed SW diurnal model, is found to be promising for measurements involving nonuniform orbital sampling characteristics.

Barkstrom, Bruce R.↗

Four dimensional observations of clouds from geosynchronous orbit using stereo display and measurement techniques on an interactive information processing system

Simultaneous Geosynchronous Operational Environmental Satellite (GOES) 1 km resolution visible image pairs can provide quantitative three dimensional measurements of clouds. These data have great potential for severe storms research and as a basic parameter measurement source for other areas of meteorology (e.g. climate). These stereo cloud height measurements are not subject to the errors and ambiguities caused by unknown cloud emissivity and temperature profiles that are associated with infrared techniques. This effort describes the display and measurement of stereo data using digital processing techniques.

Hasler, A. F.↗