Engineering topics

Zheng, Henry

Publications and source records attributed to Zheng, Henry.

3 records

DOE OSTI2025

Optimizers for stabilizing likelihood-free inference

A growing number of applications in particle physics and beyond use neural networks as unbinned likelihood ratio estimators applied to real or simulated data. Precision requirements on the inference tasks demand a high-level of stability from these networks, which are affected by the stochastic nature of training. We show how physics concepts can be used to stabilize network training through a physics-inspired optimizer. In particular, the energy conserving descent (ECD) optimization framework uses classical Hamiltonian dynamics on the space of network parameters to reduce the dependence on the initial conditions while also stabilizing the result near the minimum of the loss function. We develop a version of this optimizer known as , which has few free hyperparameters with limited ranges guided by physical reasoning. We apply to representative likelihood-ratio estimation tasks in particle physics and find on average that it out-performs the widely used Adam optimizer. We expect that ECD will be a useful tool for wide array of data-limited problems, where it is computationally expensive to exhaustively optimize hyperparameters and mitigate fluctuations with ensembling.

Monte Carlo methods↗

DOE OSTI2024

Efficiently evaluating loop integrals in the EFTofLSS using QFT integrals with massive propagators

We develop a new way to analytically calculate loop integrals in the Effective Field Theory of Large Scale-Structure. Previous available methods show severe limitations beyond the one-loop power spectrum due to analytical challenges and computational and memory costs. Our new method is based on fitting the linear power spectrum with cosmology-independent functions that resemble integer powers of quantum field theory massive propagators with complex masses. A remarkably small number of them is sufficient to reach enough accuracy. Similarly to former approaches, the cosmology dependence is encoded in the coordinate vector of the expansion of the linear power spectrum in our basis. We first produce cosmology-independent tensors where each entry is the loop integral evaluated on a given combination of basis vectors. For each cosmology, the evaluation of a loop integral amounts to contracting this tensor with the coordinate vector of the linear power spectrum. The 3-dimensional loop integrals for our basis functions can be evaluated using techniques familiar to particle physics, such as recursion relations and Feynman parametrization. We apply our formalism to evaluate the one-loop bispectrum of galaxies in redshift space. The final analytical expressions are quite simple and can be evaluated with little computational and memory cost. We show that the same expressions resolve the integration of all one-loop N-point function in the EFTofLSS. This method, which is originally presented here, has already been applied in the first one-loop bispectrum analysis of the BOSS data to constraint ΛCDM parameters and primordial non-Gaussianities [1, 2].

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2014

Comparative analysis of the transcriptome across distant species

The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features[1,2,3,4,5,6]. Specifically, we discovered co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we used expression patterns to align the stages in worm and fly development, finding a novel pairing between worm embryo and fly pupae, in addition to the expected embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we found that the extent of non-canonical, non-coding transcription is similar in each organism, per base-pair. Finally, we found in all three organisms the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a “universal model,” based on a single set of organism-independent parameters. Our comparison used the ENCODE-modENCODE RNA resource (Fig. ED1). This resource comprises: (1) deeply sequenced RNA-Seq data from many distinct samples from all three organisms; (2) comprehensive annotation of transcribed elements and (3) uniformly processed, standardized analysis files, focusing on non-coding transcription and expression patterns. Where practical, these datasets match comparable samples across organisms and to other types of functional genomics data. In total, the resource contains 575 different experiments containing >67B sequence reads. It encompasses many different RNA types, including poly(A)+, poly(A)- and ribosomal-RNA-depleted RNA and short and long RNA.

59 BASIC BIOLOGICAL SCIENCES↗