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DOE OSTI2024

The DESI one-per cent survey: exploring the halo occupation distribution of luminous red galaxies and quasi-stellar objects with AbacusSummit

ABSTRACT We present the first comprehensive halo occupation distribution (HOD) analysis of the Dark Energy Spectroscopic Instrument (DESI) One-Percent Survey luminous red galaxy (LRG) and Quasi Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 < r < 32 h−1 Mpc in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 < z < 0.6, we infer a satellite fraction of $f_\mathrm{sat} = 11\pm 1~{y{\ \mathrm{per\,cent}}}$, a mean halo mass of $\log _{10}\overline{M}_h/M_\odot =13.40^{+0.02}_{-0.02}$, and a linear bias of $b_\mathrm{lin} = 1.93_{-0.04}^{+0.06}$. For LRGs in 0.6 < z < 0.8, we find $f_\mathrm{sat}=14\pm 1~{{\ \mathrm{per\,cent}}}$, $\log _{10}\overline{M}_h/M_\odot =13.24^{+0.02}_{-0.02}$, and $b_\mathrm{lin}=2.08_{-0.03}^{+0.03}$. For QSOs, we infer $f_\mathrm{sat}=3^{+8}_{-2}\mathrm{per\,cent}$, $\log _{10}\overline{M}_h/M_\odot = 12.65^{+0.09}_{-0.04}$, and $b_\mathrm{lin} = 2.63_{-0.26}^{+0.37}$ in redshift range 0.8 < z < 2.1. Using these fits, we generate a large suite of high fidelity galaxy mocks, forming the basis of systematic tests for DESI Y1 cosmological analyses. We also study the redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealling significant and interesting trends in mean halo mass, linear bias, and satellite fraction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

BAT AGN Spectroscopic Survey – XIII. The nature of the most luminous obscured AGN in the low-redshift universe

In this paper, we present a multiwavelength analysis of 28 of the most luminous low-redshift narrow-line, ultra-hard X-ray-selected active galactic nuclei (AGN) drawn from the 70-month Swift /BAT all-sky survey, with bolometric luminosities of $\log (L_{\rm bol} /{\rm erg\, s}^{-1}) \gtrsim 45.25$. The broad goal of our study is to determine whether these objects have any distinctive properties, potentially setting them aside from lower luminosity obscured AGN in the local Universe. Our analysis relies on the first data release of the BAT AGN Spectroscopic Survey (BASS/DR1) and on dedicated observations with the VLT, Palomar, and Keck observatories. We find that the vast majority of our sources agree with commonly used AGN selection criteria which are based on emission line ratios and on mid-infrared colours. Our AGN are pre-dominantly hosted in massive galaxies (9.8 ≲ log (M*/M ⊙ ) ≲ 11.7); based on visual inspection of archival optical images, they appear to be mostly ellipticals. Otherwise, they do not have distinctive properties. Their radio luminosities, determined from publicly available survey data, show a large spread of almost four orders of magnitude – much broader than what is found for lower X-ray luminosity obscured AGN in BASS. Moreover, our sample shows no preferred combination of black hole masses ( M BH ) and/or Eddington ratio (λ Edd , covering 7.5 ≲ log ( M BH /M ⊙ ) ≲ 10.3 and 0.01 ≲ λ Edd ≲ 1. Based on the distribution of our sources in the λ Edd - N H plane, we conclude that our sample is consistent with a scenario where the amount of obscuring material along the line of sight is determined by radiation pressure exerted by the AGN on the dusty circumnuclear gas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

From the outside looking in: what can Milky Way analogues tell us about the star formation rate of our own galaxy?

ABSTRACT The Milky Way has been described as an anaemic spiral, but is its star formation rate (SFR) unusually low when compared to its peers? To answer this question, we define a sample of Milky Way analogues (MWAs) based on stringent cuts on the best literature estimates of non-transient structural features for the Milky Way. This selection yields only 176 galaxies from the whole of the SDSS DR7 spectroscopic sample which have morphological classifications in Galaxy Zoo 2, from which we infer SFRs from two separate indicators. The mean SFRs found are $\log (\rm {SFR}_{SED}/\rm {M}_{\odot }~\rm {yr}^{-1})=0.53$ with a standard deviation of 0.23 dex from SED fits, and $\log (\rm {SFR}_{W4}/\rm {M}_{\odot }~\rm {yr}^{-1})=0.68$ with a standard deviation of 0.41 dex from a mid-infrared calibration. The most recent estimate for the Milky Way’s SFR of $\log (\rm {SFR}_{MW}/\rm {M}_{\odot }~\rm {yr}^{-1})=0.22$ fits well within 2$\sigma$ of these values, where $\sigma$ is the standard deviation of each of the SFR indicator distributions. We infer that the Milky Way, while being a galaxy with a somewhat low SFR, is not unusual when compared to similar galaxies.

Fraser-McKelvie, Amelia↗
DOE OSTI2025

Synthesis of single-qutrit circuits from Clifford+𝑅 gates

Here, we present two deterministic compilation algorithms for single-qutrit unitaries with O ( log 1 / ɛ ) gate depth. Each algorithm selects a nearby approximation to the target unitary and then exactly synthesizes the approximation over the Clifford + R basis. The first algorithm exhaustively searches over the group; while the second algorithm searches only for Householder reflections. The exhaustive search algorithm yields an average R count of 2.193 ( 11 ) + 8.621 ( 7 ) log 10 ( 1 / ɛ ) , albeit with a time complexity of O ( ɛ − 4.4 ) . The Householder search algorithm results in a larger average R count of 3.20 ( 13 ) + 10.77 ( 3 ) log 10 ( 1 / ɛ ) at a reduced time complexity of O ( ɛ − 0.42 ) , greatly extending the reach in ɛ . These costs correspond asymptotically to 35% and 69% more non-Clifford gates compared with synthesizing the same unitary with two qubits. Such initial results are encouraging for using the R gate as the nontransversal gate for qutrit-based computation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Spectral-density estimation with the Gaussian integral transform

The spectral-density operator $\hat{ρ}(ω) = δ(ω–\hat{H})$ plays a central role in linear response theory as its expectation value, the dynamical response function, can be used to compute scattering cross sections. In this work, we describe a near optimal quantum algorithm providing an approximation to the spectral density with energy resolution $\Delta$ and error $\epsilon$ using $O(\sqrt{\text{log}_2 (1/ε)[\text{log}_2 (1 / Δ) + \text{log}_2 (1/ε)]/ Δ)}$ operations. This is achieved without using expensive approximations to the time-evolution operator, but instead exploiting qubitization to implement an approximate Gaussian integral transform of the spectral density. Finally, we also describe appropriate error metrics to assess the quality of the spectral function approximations more generally.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Digitization of scalar fields for quantum computing

Qubit, operator, and gate resources required for the digitization of lattice λΦ 4 scalar field theories onto quantum computers are considered, building upon the foundational work by Jordan et al. [Quantum Inf. Comput. 14, 1014 (2014); Science 336, 1130 (2012)], with a focus towards noisy intermediate-scale quantum devices. The Nyquist-Shannon sampling theorem, introduced in this context by Macridin et al. [Phys. Rev. A 98, 042312 (2018)] building on the work of Somma [Quantum Inf. Comput. 16, 1125 (2016)], provides a guide with which to evaluate the efficacy of two field-space bases, the eigenstates of the field operator, as used by Jordan et al., and eigenstates of a harmonic oscillator, to describe ( 0 + 1 )- and ( d + 1 )-dimensional scalar field theory. We show how techniques associated with improved actions, which are heavily utilized in lattice QCD calculations to systematically reduce lattice-spacing artifacts, can be used to reduce the impact of the field digitization in λΦ 4 , but are found to be inferior to a complete digitization improvement of the Hamiltonian using a quantum Fourier transform. When the Nyquist-Shannon sampling theorem is satisfied, digitization errors scale as | log | log | ε dig | | | ~ n Q (number of qubits describing the field at a given spatial site) for the low-lying states, leaving the familiar power-law lattice-spacing and finite-volume effects that scale as | log | ε latt | | ~ N Q (total number of qubits in the simulation). For localized (delocalized) field-space wave functions, it is found that n Q ~ 4 ( 7 ) qubits per spatial lattice site are sufficient to reduce theoretical digitization errors below error contributions associated with approximation of the time-evolution operator and noisy implementation on near-term quantum devices. Only classical computing resources have been used to obtain the results presented in this work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Constraints on f ( R ) and normal-branch Dvali-Gabadadze-Porrati modified gravity model parameters with cluster abundances and galaxy clustering

In this report we present forecasted cosmological constraints from combined measurements of galaxy cluster abundances from the Simons Observatory and galaxy clustering from a DESI-like experiment on two well-studied modified gravity models, the chameleon-screened Hu-Sawicki f(R) model and the nDGP braneworld Vainshtein model. A Fisher analysis is conducted using σ 8 constraints derived from thermal Sunyaev-Zel’dovich (tSZ) selected galaxy clusters as well as linear and quasilinear redshift-space 2-point galaxy correlation functions. We find that the cluster abundances drive the constraints on the nDGP model while f(R) constraints are led by galaxy clustering. The two tracers of the cosmological gravitational field are found to be complementary, and their combination significantly improves constraints on the f(R) in particular in comparison to each individual tracer alone. For a model of f(R) with a general relativity (GR) fiducial case (f R0 = 0), we find a 2-σ upper limit of f R0 ≤ 5.68 x10 -7 . For the well-studied log-based fiducial parameter value in f(R), log 10 (f R0 ) = -5, paired with the parameter value n = 1, we find combined 1-σ constraints of σ(log 10 (f R0 )) = 0.12 and σ(n) = 0.36. For the nDGP model with fiducial n nDGP = 1 we find σ( n nDGP ) = 0.087. Our results present the exciting potential to utilize upcoming galaxy and CMB survey data available in the near future to discern and/or constrain cosmic deviations from GR.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Soft-Collinear Mode for Jet Rates in Soft-Collinear Effective Theory

We propose the addition of a new "soft-collinear" mode to soft collinear effective theory (SCET) below the usual soft scale to factorize and resum logarithms of jet radii R in jet cross sections. We consider exclusive 2-jet cross sections in e + e - collisions with an energy veto Λ on additional jets. The key observation is that there are actually two pairs of energy scales whose ratio is R: the transverse momentum QR of the energetic particles inside jets and their total energy Q, and the transverse momentum ΛR of soft particles that are cut out of the jet cones and their energy Λ. The soft-collinear mode is necessary to factorize and resum logarithms of the latter hierarchy. We show how this factorization occurs in the jet thrust cross section for cone and k T -type algorithms at O(α s ) and using the thrust cone algorithm at O(α$2\atop{s}$). We identify the presence of hard-collinear, in-jet soft, global (veto) soft, and soft-collinear modes in the jet thrust cross section. We also observe here that the in-jet soft modes measured with thrust are actually the "csoft" modes of the theory SCET + . We dub the new theory with both csoft and soft-collinear modes "SCET ++ ". We go on to explain the relation between the "unmeasured" jet function appearing in total exclusive jet cross sections and the hard-collinear and csoft functions in measured jet thrust cross sections. We do not resum logs that are non-global in origin, arising from the ratio of the scales of soft radiation whose thrust is measured at Q${{\tau}}$/R and of the soft-collinear radiation at 2ΛR. Their resummation would require the introduction of additional operators beyond those we consider here. The steps we outline here are a necessary part of summing logs of R that are global in nature and have not been factorized and resummed beyond leading-log level previously.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Slow dynamics in a single bead with mechanical conditioning and transient heating

The contact stiffness of an aluminum bead confined between two slabs diminishes upon mechanical conditioning, and then recovers like log(t) after the conditioning ceases. Here that structure is evaluated for its response to transient heating and cooling, with and without accompanying conditioning vibrations. It is found that, under heating or cooling alone, stiffness changes are mostly consistent with temperature dependent material moduli; there is little or no slow dynamics. Hybrid tests in which vibration conditioning is followed by heating or cooling lead to recoveries that begin like log(t) and then become more complex. On subtracting the known response to heating or cooling alone we discern the influence of higher or lower temperatures on slow dynamic recovery from vibrations. It is found that heating accelerates the initial log(t) recovery, but by an amount more than predicted by an Arrhenius model of thermally activated barrier penetrations. Furthermore, transient cooling has no discernable effect, in contrast to the Arrhenius prediction that it slows recovery.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Rodeo Algorithm for Quantum Computing

We present a stochastic quantum computing algorithm that can prepare any eigenvector of a quantum Hamiltonian within a selected energy interval $\ [E-\epsilon, E+\epsilon]$. In order to reduce the spectral weight of all other eigenvectors by a suppression factor δ, the required computational effort scales as $\ O[|\log \delta|/(p \epsilon)]$, where p s the squared overlap of the initial state with the target eigenvector. The method, which we call the rodeo algorithm, uses auxiliary qubits to control the time evolution of the Hamiltonian minus some tunable parameter E . In this manner, we converge to the target eigenvector with exponential accuracy in the number of measurements. In addition to preparing eigenvectors, the method can also compute the full spectrum of the Hamiltonian. We illustrate the performance with several examples. For energy eigenvalue determination with error $\epsilon$, the computational scaling is $\ O[(\log \epsilon)^2/(p \epsilon)]$. For eigenstate preparation, the computational scaling is $\ O(\log \Delta/p)$, where $\Delta$ is the magnitude of the orthogonal component of the residual vector. The speed for eigenstate preparation is exponentially faster than that for phase estimation or adiabatic evolution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Generalized Quantum Signal Processing

Quantum signal processing (QSP) and quantum singular value transformation (QSVT) currently stand as the most efficient techniques for implementing functions of block-encoded matrices, a central task that lies at the heart of most prominent quantum algorithms. However, current QSP approaches face several challenges, such as the restrictions imposed on the family of achievable polynomials and the difficulty of calculating the required phase angles for specific transformations. In this paper, we present a generalized quantum signal processing (GQSP) approach, employing general SU(2) rotations as our signal-processing operators, rather than relying solely on rotations in a single basis. Our approach lifts all practical restrictions on the family of achievable transformations, with the sole remaining condition being that | P | ≤ 1 , a restriction necessary due to the unitary nature of quantum computation. Furthermore, GQSP provides a straightforward recursive formula for determining the rotation angles needed to construct the polynomials in cases where P and Q are known. In cases where only P is known, we provide an efficient optimization algorithm capable of identifying in under a minute of GPU time, a corresponding Q for polynomials of degree on the order of 10 7 . We further illustrate GQSP simplifies QSP-based strategies for Hamiltonian simulation, offer an optimal solution to the ϵ -approximate fractional query problem that requires O ( ( 1 / δ ) + log ( 1 / ϵ ) ) queries to perform where O ( 1 / δ ) is a proved lower bound, and introduces novel approaches for implementing bosonic operators. Moreover, we propose a novel framework for the implementation of normal matrices, demonstrating its applicability through synthesis of diagonal matrices, as well as the development of a new algorithm for convolution through synthesis of circulant matrices using only O ( d log N + log 2 N ) 1 and 2-qubit gates for a filter of lengths d . Published by the American Physical Society 2024

Motlagh, Danial↗
DOE OSTI2023

Malicious Cyber Activity Detection using Zigzag Persistence

In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity, and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from various forms of malicious attacks, including network damage, data theft, and activity monitoring. We focus on the cybersecurity domain and investigate the detection of malicious activity using log data. We consider the dynamics of the log data and explore the changing topology of a hypergraph representation of this data to gain insights into the underlying activity. These hypergraphs capture complex interactions between processes, together with their temporal information. To study the changing topology we use zigzag persistence, which captures how topological features persist at multiple dimensions over time. We observe that this detects malicious activity in a cyber data set. To automate this detection we implement an autoencoder trained on a vectorization of the resulting zigzag persistence barcodes. Our experimental results demonstrate the effectiveness of the autoencoder in detecting malicious activity. Overall, this study highlights the potential of zigzag persistence and its combination with temporal hypergraphs for analyzing cybersecurity log data and detecting malicious behavior.

hypergraphs, temporal hypergraph, topological data↗
DOE OSTI2019

Combining Tensor Decompositions and Graph Analytics to Provide Cyber Situational Awareness at HPC Scale

This paper describes MADHAT (Multidimensional Anomaly Detection fusing HPC, Analytics, and Tensors), an integrated workflow that demonstrates the applicability of HPC resources to the problem of maintaining cyber situational awareness. MADHAT combines two high-performance packages: ENSIGN for large-scale sparse tensor decompositions and HAGGLE for graph analytics. Tensor decompositions isolate coherent patterns of network behavior in ways that common clustering methods based on distance metrics cannot. Parallelized graph analysis then uses directed queries on a representation that combines the elements of identified patterns with other available information (such as additional log fields, domain knowledge, network topology, whitelists and blacklists, prior feedback, and published alerts) to confirm or reject a threat hypothesis, collect context, and raise alerts. MADHAT was developed using the collaborative HPC Architecture for Cyber Situational Awareness (HACSAW) research environment and evaluated on structured network sensor logs collected from Defense Research and Engineering Network (DREN) sites using HPC resources at the U.S. Army Engineer Research and Development Center DoD Supercomputing Resource Center (ERDC DSRC). To date, MADHAT has analyzed logs with over 650 million entries.

Cyber security, Tensor decomposition, graph analyt↗
DOE OSTI2020

Understanding the Interplay between Hardware Errors and User Job Characteristics on the Titan Supercomputer

Designing dependable supercomputers begins with an understanding of errors in real-world, large-scale systems. The Titan supercomputer at Oak Ridge National Laboratory provides a unique opportunity to investigate errors when an actual system is actively used by multiple concurrent users and workloads from diverse domains at varying scales. This study presents a thorough analysis of 6, 908, 497 hardware errors from 18, 688 compute nodes of Titan for 312, 215 user jobs over a 3-year time period. Through careful joining of two system logs – the Machine Check Architecture (MCA) log and the job scheduler log – we show the correlated pattern of hardware errors for each job and user, in addition to individual descriptive statistics of errors, jobs, and users. Since the majority of hardware errors are memory errors, this study also shows the importance of error correcting in memory systems.

Lim, Seung-Hwan↗
DOE OSTI2016

PATHA: Performance Analysis Tool for HPC Applications

Large science projects rely on complex workflows to analyze terabytes or petabytes of data. These jobs are often running over thousands of CPU cores and simultaneously performing data accesses, data movements, and computation. It is difficult to identify bottlenecks or to debug the performance issues in these large workflows. In order to address these challenges, we have developed Performance Analysis Tool for HPC Applications (PATHA) using the state-of-art open source big data processing tools. Our framework can ingest system logs to extract key performance measures, and apply the most sophisticated statistical tools and data mining methods on the performance data. Furthermore, it utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of PATHA, we conduct a case study on the workflows from an astronomy project known as the Palomar Transient Factory (PTF). This study processed 1.6 TB of system logs collected on the NERSC supercomputer Edison. Using PATHA, we were able to identify performance bottlenecks, which reside in three tasks of PTF workflow with the dependency on the density of celestial objects.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

Salmonella Inactivation During Extrusion of an Oat Flour Model Food

Abstract Little research exists on Salmonella inactivation during extrusion processing, yet many outbreaks associated with low water activity foods since 2006 were linked to extruded foods. The aim of this research was to study Salmonella inactivation during extrusion of a model cereal product. Oat flour was inoculated with Salmonella enterica serovar Agona, an outbreak strain isolated from puffed cereals, and processed using a single‐screw extruder at a feed rate of 75 kg/h and a screw speed of 500 rpm. Extrudate samples were collected from the barrel outlet in sterile bags and immediately cooled in an ice–water bath. Populations were determined using standard plate count methods or a modified most probable number when populations were low. Reductions in population were determined and analyzed using a general linear model. The regression model obtained for the response surface tested was Log ( N R / N O ) = 20.50 + 0.82 T − 141.16a w – 0.0039 T 2 + 87.91 a w 2 ( R 2 = 0.69). The model showed significant ( p < 0.05) linear and quadratic effects of a w and temperature and enabled an assessment of critical control parameters. Reductions of 0.67 ± 0.14 to 7.34 ± 0.02 log CFU/g were observed over ranges of a w (0.72 to 0.96) and temperature (65 to 100 °C) tested. Processing conditions above 82 °C and 0.89 a w achieved on average greater than a 5‐log reduction of Salmonella . Results indicate that extrusion is an effective means for reducing Salmonella as most processes commonly employed to produce cereals and other low water activity foods exceed these parameters. Thus, contamination of an extruded food product would most likely occur postprocessing as a result of environmental contamination or through the addition of coatings and flavorings.

Anderson, Nathan M.↗
DOE OSTI2023

Morphological traits for allometric scaling of the European Sea Bass Dicentrarchus labrax (Linnaeus, 1758) from Southern Portugal population

Abstract The present study aimed to determine the allometric scaling among a selection of morphological traits in European sea bass ( Dicentrarchus labrax ) to estimate fish body weight. A set of morphological traits (fish body weight, length, height, and width) were directly measured in 146 fish of a recirculating aquaculture system, with body weights ranging from 17.11 to 652.21 g. In addition, a collection of digital imagery of each anesthetized fish from the side and top views were used to estimate other traits (indirect measures). Multiple regression analysis and regression coefficients were calculated using all possible combinations of biometric data (predictors) to estimate fish body weight, applying different numerical fitting models (linear, log‐linear, quadratic, exponential). The results showed that the best combination of traits for estimating fish body weight were fish body width, length and height, collected from direct measure ( R 2 = 0.995), for a log‐linear model fitting, which revealed more accurate determinations than the most commonly used length–weight relationship. Nevertheless, other combinations of morphological traits and fitting models were also found to be suitable in successfully predict fish body weight, with variability ranging between 92.5% and 98.5%. For indirect measures, the best predictor was a combination of traits from top view (width, eye distance and area without fins) fitted with a log‐linear function. These results comprise a relevant baseline in supporting the high potential of noninvasive methods to accurately follow the growth of European sea bass juveniles, recurring to imagery analysis of anesthetized fish. It has major potential applications in feeding consumption trials and fish growth models, as it allows for continuously following up fish growth under different experimental conditions without therein distress derived from manipulation.

Azevedo, Ana↗
DOE OSTI2025

Fate of Listeria monocytogenes Serotypes on Frozen Mixed Vegetables During Consumer‐Simulated Thawing and Storage

ABSTRACT Recent outbreaks and recalls associated with frozen vegetables in the United States and Europe have been linked to Listeria monocytogenes . This study aims to understand the extent to which frozen vegetables support the growth of L. monocytogenes once thawed and held at different temperatures. Six L. monocytogenes strains, two of each from serotypes 1/2a, 1/2b, and 4b, were individually inoculated onto frozen vegetables and stored at −18°C for 7 days. After 7 days, the vegetables were thawed and stored at 5°C or 10°C for up to 14 days or at 25°C for up to 7 days. L. monocytogenes was enumerated from the thawed vegetables throughout the storage period. Population data were fitted to the primary Baranyi model to estimate growth rates and lag phase durations; the secondary Ratkowsky square root model was used to model the relationship of the growth rates with storage temperature. Five of the L. monocytogenes strains survived and grew on the thawed vegetables (population increases of > 1 log CFU/g) stored at 5°C, and all six of the strains proliferated at 10°C and 25°C (population increases of > 3 log CFU/g after 14 days and > 4 log CFU/g after 7 days, respectively). A secondary model was successfully generated based on the growth rates of the six L. monocytogenes strains on the thawed vegetables ( r 2 = 0.8888, RMSE = 0.2057). Results from this study fill a data gap associated with L. monocytogenes survival on thawed vegetables and can be used to determine safe handling and storage practices for these products to protect public health.

Salazar, Joelle K. [Division of Food Processing Sc↗