Observing the emergence of chaos in a many-particle quantum system

Accessing the connection between classical chaos and quantum many-body systems has been a long-standing experimental challenge. Here, we investigate the onset of chaos in periodically driven two-component Bose-Einstein condensates, whose small quantum uncertainties allow for exploring the phase space with high resolution. By analyzing the uncertainties of time-evolved many-body states, we find signatures of elliptic and hyperbolic periodic orbits generated according to the Poincar\'e-Birkhoff theorem, and the formation of a chaotic region at increasing driving strengths. The employed fluctuation analysis allows for probing the phase-space structure by use of only short-time quantum dynamics.Comment: 5+2 pages, 4 figure

Complex paths for regular-to-chaotic tunneling rates

In generic Hamiltonian systems tori of regular motion are dynamically separated from regions of chaotic motion in phase space. Quantum mechanically these phase-space regions are coupled by dynamical tunneling. We introduce a semiclassical approach based on complex paths for the prediction of dynamical tunneling rates from regular tori to the chaotic region. This approach is demonstrated for the standard map giving excellent agreement with numerically determined tunneling rates.Comment: 5 pages, 4 figure

Open Mushrooms: Stickiness revisited

We investigate mushroom billiards, a class of dynamical systems with sharply divided phase space. For typical values of the control parameter of the system $\rho$, an infinite number of marginally unstable periodic orbits (MUPOs) exist making the system sticky in the sense that unstable orbits approach regular regions in phase space and thus exhibit regular behaviour for long periods of time. The problem of finding these MUPOs is expressed as the well known problem of finding optimal rational approximations of a real number, subject to some system-specific constraints. By introducing a generalized mushroom and using properties of continued fractions, we describe a zero measure set of control parameter values $\rho\in(0,1)$ for which all MUPOs are destroyed and therefore the system is less sticky. The open mushroom (billiard with a hole) is then considered in order to quantify the stickiness exhibited and exact leading order expressions for the algebraic decay of the survival probability function $P(t)$ are calculated for mushrooms with triangular and rectangular stems.Comment: 21 pages, 11 figures. Includes discussion of a three-dimensional mushroo

The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights

Standardizing convolutional filters that enhance specific structures and patterns in medical imaging enables reproducible radiomics analyses, improving consistency and reliability for enhanced clinical insights. Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decision support tools. In this special report, teams of researchers who developed radiomics software participated in a three-phase study (September 2020 to December 2022) to establish a standardized set of filters. The first two phases focused on finding reference filtered images and reference feature values for commonly used convolutional filters: mean, Laplacian of Gaussian, Laws and Gabor kernels, separable and nonseparable wavelets (including decomposed forms), and Riesz transformations. In the first phase, 15 teams used digital phantoms to establish 33 reference filtered images of 36 filter configurations. In phase 2, 11 teams used a chest CT image to derive reference values for 323 of 396 features computed from filtered images using 22 filter and image processing configurations. Reference filtered images and feature values for Riesz transformations were not established. Reproducibility of standardized convolutional filters was validated on a public data set of multimodal imaging (CT, fluorodeoxyglucose PET, and T1-weighted MRI) in 51 patients with soft-tissue sarcoma. At validation, reproducibility of 486 features computed from filtered images using nine configurations × three imaging modalities was assessed using the lower bounds of 95% CIs of intraclass correlation coefficients. Out of 486 features, 458 were found to be reproducible across nine teams with lower bounds of 95% CIs of intraclass correlation coefficients greater than 0.75. In conclusion, eight filter types were standardized with reference filtered images and reference feature values for verifying and calibrating radiomics software packages. A web-based tool is available for compliance checking

Integrated radiogenomics analyses allow for subtype classification and improved outcome prognosis of patients with locally advanced HNSCC.

Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) may benefit from personalised treatment, requiring biomarkers that characterize the tumour and predict treatment response. We integrate pre-treatment CT radiomics and whole-transcriptome data from a multicentre retrospective cohort of 206 patients with locally advanced HNSCC treated with primary radiochemotherapy to classify tumour molecular subtypes based on radiomics, develop surrogate radiomics signatures for gene-based signatures related to different biological tumour characteristics and evaluate the potential of combining radiomics features with full-transcriptome data for the prediction of loco-regional control (LRC). Using end-to-end machine-learning, we developed and validated a model to classify tumours of the atypical subtype (AUC [95% confidence interval] 0.69 [0.53-0.83]) based on CT imaging, observed that CT-based radiomics models have limited value as surrogates for six selected gene signatures (AUC < 0.60), and showed that combining a radiomics signature with a transcriptomics signature consisting of two metagenes representing the hedgehog pathway and E2F transcriptional targets improves the prognostic value for LRC compared to both individual sources (validation C-index [95% confidence interval], combined: 0.63 [0.55-0.73] vs radiomics: 0.60 [0.50-0.71] and transcriptomics: 0.59 [0.49-0.69]). These results underline the potential of multi-omics analyses to generate reliable biomarkers for future application in personalized oncology

Biomarker signatures for primary radiochemotherapy of locally advanced HNSCC - hypothesis generation on a multicentre cohort of the DKTK-ROG.

PURPOSE: To develop prognostic biomarker signatures for patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated by primary radiochemotherapy (RCTx) based on previously published molecular analyses of the retrospective biomarker study of the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG). MATERIAL AND METHODS: In previous studies on the retrospective DKTK-ROG HNSCC cohort treated with primary RCTx, the following clinical parameters and biomarkers were evaluated and found to be significantly associated with loco-regional tumour control (LRC) or overall survival (OS): tumour volume, p16 status, expression of cancer stem cell markers CD44 and SLC3A2, expressions of hypoxia-associated gene signatures, tumour mutational burden (TMB), single nucleotide polymorphisms (SNPs) in the ERCC2 gene (rs1799793, rs13181) and ERCC5 gene (rs17655) as well as the expression of CXCR4, SDF-1 and CD8. These biomarkers were combined in multivariable modelling using Cox-regression with backward variable selection. RESULTS: A baseline signature containing the widely accepted parameters tumour volume, p16 status, cancer stem cell marker expression (CD44) and hypoxia-associated gene expression has been defined, representing the main hypothesis of the study. Furthermore, the baseline signature was extended by additional prognostic biomarkers and a data-driven signature without any pre-hypothesis was generated for both endpoints. In these signatures, the SNPs rs1799793 and rs17655 as well as CXCR4, SDF-1 and SLC3A2 expression were additionally included. The signatures showed significant patient stratifications for LRC and OS. CONCLUSION: Three biomarker signatures were defined for patients with locally advanced HNSCC treated with primary RCTx for the endpoints LRC and OS. These signatures will be validated in the prospective HNprädBio study of the DKTK-ROG that recently completed recruitment, before potential application in an interventional trial