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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Engineering Scale Drying of Aluminum-Clad Spent Nuclear Fuel: Experiment Report

Engineering-scale tests were performed to evaluate the relative effectiveness of forced gas and vacuum-drying processes on aluminum-clad spent nuclear fuel (ASNF) in preparation for extended dry storage. Drying models were developed to improve confidence in the likely range of conditions at the start of dry storage and to understand the factors most significant to each process. Testing was performed at the Holtec International Forced Helium Dehydration training facility in Camden, New Jersey, by students from the University of South Carolina in collaboration with Idaho National Laboratory. A full-size Type 1a basket, with a full-diameter vessel configuration (based on the Department of Energy standardized canister design), was used in combination with a 10 assembly surrogate ASNF arrangement to provide a proxy for geometry. A resistance heater incorporated in one assembly simulated the influence of 100 W decay heat. This instrumented chamber allowed testing of the removal of bulk water, physisorbed water, and chemisorbed water over a range of operating parameters with either drying process. Thick oxide films were grown on aluminum test plates to mimic the ASNF surface chemistry. These one-use test plates were housed within select assemblies during drying. Post-test analysis of these plates gave a measure of the moisture removed during each test, which was compared to a control. Instrumentation provided detailed thermal, humidity, and gas or pressure data relevant to each test. Model simulations generally compared favorably to instrument data for the tests. While both processes were able to remove bulk water, removal of chemisorbed water was shown to depend heavily on local temperature. To the disadvantage of vacuum drying, operations approaching or exceeding 220°C achieved consistently more dehydroxylation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Scalability of Several Asynchronous Many-Task Models for In Situ Statistical Analysis.

This report is a sequel to [PB16], in which we provided a first progress report on research and development towards a scalable, asynchronous many-task, in situ statistical analysis engine using the Legion runtime system. This earlier work included a prototype implementation of a proposed solution, using a proxy mini-application as a surrogate for a full-scale scientific simulation code. The first scalability studies were conducted with the above on modestly-sized experimental clusters. In contrast, in the current work we have integrated our in situ analysis engines with a full-size scientific application (S3D, using the Legion-SPMD model), and have conducted nu- merical tests on the largest computational platform currently available for DOE science ap- plications. We also provide details regarding the design and development of a light-weight asynchronous collectives library. We describe how this library is utilized within our SPMD- Legion S3D workflow, and compare the data aggregation technique deployed herein to the approach taken within our previous work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Measurement of correlations among net-charge, net-proton, and net-kaon multiplicity distributions in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

Correlations among conserved quantum numbers, such as the net-electric charge, the net-baryon, and the net-strangeness in heavy-ion collisions, are crucial for exploring the QCD phase diagram. In this paper, these correlations are investigated using net-proton number (as a proxy for the net-baryon), net-kaon number (for the net-strangeness), and net-charged particle number in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV with the ALICE detector. The observed correlations deviate from the Poissonian baseline, with a more pronounced deviation at LHC energies than at RHIC. Theoretical calculations of the Thermal-FIST hadron resonance gas model, HIJING, and EPOS LHC event generators are compared with experimental results, where a significant impact of resonance decays is observed. Thermal-FIST calculations under the grand canonical and canonical ensembles highlight significant differences, underscoring the role of local charge conservation in explaining the data. Recent lattice QCD studies have demonstrated that the magnetic field generated by spectator protons in heavy-ion collisions affects susceptibility ratios, in particular those related to the net-electric charge and the net-baryon numbers. The experimental findings are in qualitative agreement with the expectations of lattice QCD.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Mesoscale modeling of hypervelocity impacts using the CTH shock physics code

Material fragmentation after a hypervelocity impact is vital to predictive electro-optical and infrared (EO/IR) modeling. Successful comparisons with data require that hot, submicron fragments are generated in such impacts; yet, experimental data has so far been unable to produce fragments of this scale. The purpose of this work was to investigate how modeling assumptions of macro-scale, bulk materials might influence the generation of debris in hypervelocity impacts and ultimately the predicted EO/IR signatures of these debris clouds. Sphere-on-plate impact simulations simplified the comparison of different modeling approaches. In one set of simulations, materials were modeled with the traditional, bulk approach. Those findings were compared to simulations run with the mesoscale material grain structure explicitly modeled. This study focused on the comparison of two parameters that are tied directly to the EO/IR signature: strain rate at failure (a proxy for debris fragment size) and material temperature. Interfaces between grains, here due to void insertion, resulted in the most notable change in both the strain rate at failure and material temperature. Shock reflections from grain-void interfaces induced higher strain rates and material temperatures, and it is expected that similar effects may be produced from inclusions or dislocations in real materials. Thus, interfaces within a material may play an important role in producing smaller hot debris frag

42 ENGINEERING↗
DOE OSTI2023

Accounting for Changes in Radiation Improves the Ability of SIF to Track Water Stress-Induced Losses in Summer GPP in a Temperate Deciduous Forest

Global observations of solar-induced chlorophyll fluorescence (SIF) are available from multiple satellite platforms, and SIF is increasingly used as a proxy for photosynthetic activity and ecosystem productivity. Because the relationship between SIF and gross primary productivity (GPP) depends on a variety of factors including ecosystem type and environmental conditions, it is necessary to study SIF observations across various spatiotemporal scales and ecosystems. To explore how SIF signals relate to productivity over a temperate deciduous forest, we deployed a PhotoSpec spectrometer system at the University of Michigan Biological Station AmeriFlux site (US-UMB) in the northern Lower Peninsula of Michigan during the 2018 and 2019 growing seasons. We found that SIF correlated with GPP across diurnal and seasonal cycles (R 2 = 0.61 and 0.64 for 90-min- and daily-averaged data), but that SIF signals were more strongly related to downwelling radiation than GPP (R 2 = 0.91 for daily-averaged data). The dependence of SIF on radiation obscured the impact of intraseasonal drought in the SIF timeseries, but drought stress was apparent as a decrease in relative SIF, which exhibited a stronger correlation with GPP (R 2 = 0.56) than other remotely sensed data over the drought period. These results highlight the potential of SIF for detecting stress-induced losses in forest productivity. Additionally, we found that the red:far-red SIF ratio did not exhibit a response to water stress-induced losses in productivity, but was largely driven by seasonal and interannual changes in canopy structure, as well as by synoptic changes in downwelling radiation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Probing the galaxy–halo connection with total satellite luminosity

ABSTRACT We demonstrate how the total luminosity in satellite galaxies is a powerful probe of dark matter haloes around central galaxies. The method cross-correlates central galaxies in spectroscopic galaxy samples with fainter galaxies detected in photometric surveys. Using models, we show that the total galaxy luminosity, Lsat, scales linearly with host halo mass, making Lsat an excellent proxy for Mh. Lsat is also sensitive to the formation time of the halo. We demonstrate that probes of galaxy large-scale environment can break this degeneracy. Although this is an indirect probe of the halo, it yields a high signal-to-noise ratio measurement for galaxies expected to occupy haloes at <1012 M⊙, where other methods suffer from larger errors. In this paper, we focus on observational and theoretical systematics in the Lsat method. We test the robustness of our method of finding central galaxies and our methods of estimating the number of background galaxies. We implement this method on galaxies in the Sloan Digital Sky Survey (SDSS) data, with satellites identified in fainter imaging data. We find excellent agreement between our theoretical predictions and the observational measurements. Finally, we compare our Lsat measurements to weak lensing estimates of Mh for red and blue subsamples. In the stellar mass range where the measurements overlap, we find consistent results, where red galaxies live in larger haloes. However, the Lsat approach allows us to probe significantly lower mass galaxies. At these masses, the Lsat values are equivalent. This example shows the potential of Lsat as a probe of dark haloes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Iterative sampling of expensive simulations for faster deep surrogate training

Deep neural network (DNN) surrogates of expensive physics simulations are enabling a rapid change in the way that common experimental design and analysis tasks are approached. Surrogate models allow simulations to be performed in parallel and separately from downstream tasks, thereby enabling analyses that would be impossible with the simulation in-the-loop; surrogates based on DNNs can effectively emulate diverse non-scalar data of the types collected in fusion and laboratory-astrophysics experiments. The challenge is in training the surrogate model, for which large ensembles of physics simulations must be run, preferably without wasting computational effort on uninteresting simulations. Here, in this paper, we present an iterative sampling scheme that can preferentially propose simulations in interesting regions of parameter space without neglecting unexplored regions, allowing high-quality and wide-ranging surrogate models to be trained using 2–3 times fewer simulations compare to space-filling designs. Our approach uses an explicit importance function defined on the simulation output space, balanced against a measure of simulation density which serves as a proxy for surrogate accuracy. It is easy to implement and can be tuned to find interesting simulations early in the study, allowing surrogates to be trained quickly and refined as new simulations become available; this represents an important step towards the routine generation of deep surrogate models quickly enough to be truly relevant to experimental work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Geochemical and multi-isotopic ( 87 Sr/ 86 Sr, 143 Nd/ 144 Nd, 238 U/ 235 U) perspectives of sediment sources, depositional conditions, and diagenesis of the Marcellus Shale, Appalachian Basin, USA

Here, we investigate sediment sources, depositional conditions and diagenetic processes affecting the Middle Devonian Marcellus Shale in the Appalachian Basin, eastern USA, a major target of natural gas exploration. Multiple proxies, including trace metal contents, rare earth elements (REE), the Sm-Nd and Rb-Sr isotope systems, and U isotopes were applied to whole rock digestions and sequentially extracted fractions of the Marcellus shale and adjacent units from two locations in the Appalachian Basin. The narrow range of εNd values (from –7.8 to –6.4 at 390 Ma) is consistent with derivation of the clastic sedimentary component of the Marcellus Shale from a well-mixed source of fluvial and eolian material of the Grenville orogenic belt, and indicate minimal post-depositional alteration of the Sm-Nd system. While silicate minerals host >80% of the REE in the shale, data from sequentially extracted fractions reflect post-depositional modifications at the mineralogical scale, which is not observed in whole rock REE patterns.

58 GEOSCIENCES↗
DOE OSTI2019

O(N) Quantum Molecular Dynamics (QMD) Algorithms, Code Requirements, Release Notes, and Library Deployment

The Exascale Computing Project (ECP) Co-design Center for Particle Applications (CoPA) is addressing the challenges for particle applications to run on upcoming exascale computing architectures. This includes short- and long-range molecular dynamics (MD), particle-in-cell (PIC), and quantum molecular dynamics (QMD). This document addresses $\mathcal{O}(N)$ QMD. The goal of this CoPA team is to develop $\mathcal{O}(N)$ linear scaling methods for QMD optimized for new and next generation architectures. This will provide the capability to simulate larger systems and run for longer timeframes than is possible today. Focus is initially on the density matrix construction. This requires efficient matrix formats and linear algebra operations for distributed architectures. A significant reduction in the wallclock time for an MD timestep is necessary to achieve practical large scale QMD. Equally challenging is to develop scalable distributed implementations. This requires the exploration of efficient data formats (dense, sparse, etc.), data decomposition and distribution across compute nodes using block- and graph-based methods. Traditional programming models such as MPI/OpenMP, hybrid MPI/OpenMP/Accelerator, as well as asynchronous task-based models will be explored to achieve maximum parallelism. Parallelism at the level of a matrix operation, solver, and/or application needs to be explored to gain the most benefit on new and emerging architectures. This report serves as a “living document” of the additions and enhancements throughout the ECP CoPA project for $\mathcal{O}(N)$ QMD. The following sections address the applications we are working with, the quantum chemistry libraries (BML and PROGRESS), and our co-design exploration through the use of a proxy application.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Real-World Driving Features for Identifying Intelligent Driver Model Parameters

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. Although the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “intelligent driver model” (IDM) as our driver behavior model and use real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations, and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2021

Real-World Driving Features for Identifying Intelligent Driver Model Parameters: Preprint

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. While the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “Intelligent Driver Model” (IDM) as the driver behavior model to explore and real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2022

BASS XXXII: Studying the Nuclear Millimeter-wave Continuum Emission of AGNs with ALMA at Scales ≲100–200 pc

To understand the origin of nuclear (≲100 pc) millimeter-wave (mm-wave) continuum emission in active galactic nuclei (AGNs), we systematically analyzed subarcsecond resolution Band-6 (211–275 GHz) Atacama Large Millimeter/submillimeter Array data of 98 nearby AGNs (z < 0.05) from the 70 month Swift/BAT catalog. The sample, almost unbiased for obscured systems, provides the largest number of AGNs to date with high mm-wave spatial resolution sampling (~1–200 pc), and spans broad ranges of 14–150 keV luminosity {$40\lt \mathrm{log}[{L}_{14-150}/(\mathrm{erg}\,{{\rm{s}}}^{-1})]\lt 45$}, black hole mass $[5\lt \mathrm{log}({M}_{\mathrm{BH}}/{M}_{\odot })\lt 10$], and Eddington ratio ($-4\lt \mathrm{log}{\lambda }_{\mathrm{Edd}}\lt 2$). We find a significant correlation between 1.3 mm (230 GHz) and 14–150 keV luminosities. Its scatter is ≈0.36 dex, and the mm-wave emission may serve as a good proxy of the AGN luminosity, free of dust extinction up to N H ~ 10 26 cm –2 . While the mm-wave emission could be self-absorbed synchrotron radiation around the X-ray corona according to past works, we also discuss different possible origins of the mm-wave emission: AGN-related dust emission, outflow-driven shocks, and a small-scale (<200 pc) jet. The dust emission is unlikely to be dominant, as the mm-wave slope is generally flatter than expected. Also, due to no increase in the mm-wave luminosity with the Eddington ratio, a radiation-driven outflow model is possibly not the common mechanism. Furthermore, we find independence of the mm-wave luminosity on indicators of the inclination angle from the polar axis of the nuclear structure, which is inconsistent with a jet model whose luminosity depends only on the angle.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Beam energy dependence of net- Λ fluctuations measured by the STAR experiment at the BNL Relativistic Heavy Ion Collider

The measurements of particle multiplicity distributions have generated considerable interest in understanding the fluctuations of conserved quantum numbers in the quantum chromodynamics (QCD) hadronization regime, in particular near a possible critical point and near the chemical freeze-out. Net-protons and net-kaons have been used as proxies for the net-baryon number and net-strangeness, respectively. We report the measurement of efficiency- and centrality-bin width-corrected cumulant ratios (C 2 /C 1 , C 3 /C 2 ) of net- Λ distributions, in the context of both strangeness and baryon number conservation, as a function of collision energy, centrality, and rapidity. The results are for Au + Au collisions at five beam energies ( √s NN = 19.6 , 27, 39, 62.4, and 200 GeV) recorded with the Solenoidal Tracker at RHIC (STAR). We compare our results to the Poisson and negative binomial (NBD) expectations, as well as to ultrarelativistic quantum molecular dynamics (UrQMD) and hadron resonance gas (HRG) model predictions. Both NBD and Poisson baselines agree with data within the statistical and systematic uncertainties. UrQMD describes the measured net- Λ C 1 and C 3 at 200 GeV reasonably well but deviates from C 2 , and the deviation increases as a function of collision energy. The ratios of the measured cumulants show no features of critical fluctuations. The chemical freeze-out temperatures extracted from a recent HRG calculation, which was successfully used to describe the net-proton, net-kaon, and net-charge data, indicate Λ freeze-out conditions similar to those of kaons. However, large deviations are found when comparing with temperatures obtained from net-proton fluctuations. The net- Λ cumulants show a weak but finite dependence on the rapidity coverage in the acceptance of the detector, which can be attributed to quantum number conservation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Photometric Characterization of the Dark Energy Camera

We characterize the variation in photometric response of the Dark Energy Camera (DECam) across its 520 Mpix science array during 4 years of operation. These variations are measured using high signal-to-noise aperture photometry of >10 7 stellar images in thousands of exposures of a few selected fields, with the telescope dithered to move the sources around the array. A calibration procedure based on these results brings the rms variation in aperture magnitudes of bright stars on cloudless nights down to 2–3 mmag, with <1 mmag of correlated photometric errors for stars separated by ≥20''. On cloudless nights, any departures of the exposure zeropoints from a secant airmass law exceeding 1 mmag are plausibly attributable to spatial/temporal variations in aperture corrections. These variations can be inferred and corrected by measuring the fraction of stellar light in an annulus between 6'' and 8'' diameter. Key elements of this calibration include: correction of amplifier nonlinearities; distinguishing pixel-area variations and stray light from quantum-efficiency variations in the flat fields; field-dependent color corrections; and the use of an aperture-correction proxy. The DECam response pattern across the 2° field drifts over months by up to ±9 mmag, in a nearly wavelength-independent low-order pattern. Here, we find no fundamental barriers to pushing global photometric calibrations toward mmag accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Quantifying Seasonal and Diurnal Cycles of Solar‐Induced Fluorescence With a Novel Hyperspectral Imager

Abstract Solar‐induced fluorescence (SIF) is a proxy of ecosystem photosynthesis that often scales linearly with gross primary productivity (GPP) at the canopy scale. However, the mechanistic relationship between GPP and SIF is still uncertain, especially at smaller temporal and spatial scales. We deployed a ultra‐hyperspectral imager over two grassland sites in California throughout a soil moisture dry down. The imager has high spatial resolution that limits mixed pixels, enabling differentiation between plants and leaves within one scene. We find that imager SIF correlates well with diurnal changes in leaf‐level physiology and gross primary productivity under well‐watered conditions. These relationships deteriorate throughout the dry down event. Our results demonstrate an advancement in SIF imaging with new possibilities in remotely sensing plant canopies from the leaf to the ecosystem. These data can be used to resolve outstanding questions regarding SIF's meaning and usefulness in terrestrial ecosystem monitoring.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

The Russian Model of Internet Control and Its Significance

Russia has emerged as an exemplar of an innovative and experimental – though not always completely consistent or successful – alternative approach to information manipulation and control that differs significantly from the more-often discussed Chinese “Great Firewall” system and other approaches with an emphasis on systemic technical censorship. The Russian model relies on a mix of less overt, more plausibly deniable, legalistic, and often non-technical mechanisms to manipulate online information flows, narratives, and framings, to affect and shape public opinion without resort to universal censorship. The government uses surveillance, a panoply of vague laws, the prosecution or censorship of exemplars, proxy actors and hard to track extra-legal pressures, hacking and leaks, and a heavy emphasis on content production and manipulation to influence narratives and shape public opinion. This model for the domestic control of information not only fits with Russia’s own political system, but is likely to prove more resonant and easier to emulate across many other countries in which a systematic-censorship approach is not technologically or politically feasible. The learning and experimentation involved in this type of domestic information manipulation also has direct applicability to the use of information operations in international political and military competition. The future of this model will likely depend on continuing innovation, not least on the leveraging of advances in artificial intelligence and big data analysis. If successful, however, this might look very different from the future of information control in China – and have significantly different repercussions for democracies and the international system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Control-oriented premixed charge compression ignition CA50 model for a diesel engine utilizing variable valve actuation

Premixed charge compression ignition (PCCI) is a promising combustion strategy for reducing in-cylinder NO x and particulate matter formation in diesel engines without incurring fuel penalty. However, one of the challenges in PCCI implementation is that the process does not allow direct control of the combustion timing. The crank angle of 50% heat release, known as the CA50, is generally a reasonable proxy for the quality of combustion in terms of maximum pressure rise rate, combustion noise, and fuel conversion efficiency. This paper outlines the development, and validation, of a real-time capable estimation strategy for diesel-fueled PCCI CA50 using production-viable measurements that do not include in-cylinder pressure. The CA50 estimation strategy considers both stages of diesel-fueled PCCI combustion—low-temperature heat release and high-temperature heat release, which contributes most to the cumulative heat released during combustion. The strategy is validated using a PCCI CA50 dataset generated with a wide range of positions of a variable geometry turbocharge, exhaust gas recirculation fractions, and intake valve closing timings. The model estimates CA50 within ±2 CAD for 65 out of 80 data points and exhibits an error standard deviation of 2.55 CAD.

Halbe, Mayura H.↗
DOE OSTI2024

Probing Postmeasurement Entanglement without Postselection

We study the problem of observing quantum collective phenomena emerging from large numbers of measurements. These phenomena are difficult to observe in conventional experiments because, in order to distinguish the effects of measurement from dephasing, it is necessary to postselect on sets of measurement outcomes with Born probabilities that are exponentially small in the number of measurements performed. An unconventional approach, which avoids this exponential “postselection problem”, is to construct cross-correlations between experimental data and the results of simulations on classical computers. However, these cross-correlations generally have no definite relation to physical quantities. We first show how to incorporate classical shadows into this framework, thereby allowing for the construction of quantum information-theoretic cross-correlations. We then identify cross-correlations that both upper and lower bound the measurement-averaged von Neumann entanglement entropy, as well as cross-correlations that lower bound the measurement-averaged purity and entanglement negativity. These bounds show that experiments can be performed to constrain postmeasurement entanglement without the need for postselection. To illustrate our technique, we consider how it could be used to observe the measurement-induced entanglement transition in Haar-random quantum circuits. We use exact numerical calculations as proxies for quantum simulations and, to highlight the fundamental limitations of classical memory, we construct cross-correlations with tensor-network calculations at finite bond dimension. Our results reveal a signature of measurement-induced criticality that can be observed using a quantum simulator in polynomial time and with polynomial classical memory. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗