Quantum simulation of Maxwell's equations via Schr\"odingersation

We present quantum algorithms for electromagnetic fields governed by Maxwell's equations. The algorithms are based on the Schr\"odingersation approach, which transforms any linear PDEs and ODEs with non-unitary dynamics into a system evolving under unitary dynamics, via a warped phase transformation that maps the equation into one higher dimension. In this paper, our quantum algorithms are based on either a direct approximation of Maxwell's equations combined with Yee's algorithm, or a matrix representation in terms of Riemann-Silberstein vectors combined with a spectral approach and an upwind scheme. We implement these algorithms with physical boundary conditions, including perfect conductor and impedance boundaries. We also solve Maxwell's equations for a linear inhomogeneous medium, specifically the interface problem. Several numerical experiments are performed to demonstrate the validity of this approach. In addition, instead of qubits, the quantum algorithms can also be formulated in the continuous variable quantum framework, which allows the quantum simulation of Maxwell's equations in analog quantum simulation

Progress in Martian seismology and temporal changes of Martian subsurface structure

The exploration of the deep earth, deep sea, and deep space represents a major national science and technology strategy, and is also a cutting-edge research field in the world. Mars exploration falls within the realm of space exploration, whereas probing the interior of an exoplanet resembles the deep earth exploration. Consequently, exploring the subsurface structure of Mars can be considered a combination of deep space and deep earth exploration. It is of great significance to summarize and sort out the current research progress of Mars and find new research content. This article reviews the research progress of Mars seismology based on InSight data, including the new understanding of marsquakes properties and the investigation of Mars internal structure. The focus is on the background, principle and new progress of the studying on temporal velocity changes in Martian subsurface structure using the single seismic station onboard InSight and the observed diurnal and seasonal variation of seismic velocity are introduced. The influencing factors of Mars seismic velocity change are analyzed through relevant studies on the Earth and Moon. Problems and opportunities in the study of temporal changes in Martian media are also summarized. Finally, we prospect the research direction and development trend of time-varying monitoring of Martian media by using single-station method

cuPDLP-C: A Strengthened Implementation of cuPDLP for Linear Programming by C language

A recent GPU implementation of the Restarted Primal-Dual Hybrid Gradient Method for Linear Programming was proposed in Lu and Yang (2023). Its computational results demonstrate the significant computational advantages of the GPU-based first-order algorithm on certain large-scale problems. The average performance also achieves a level close to commercial solvers for the first time in history. However, due to limitations in experimental hardware and the disadvantage of implementing the algorithm in Julia compared to C language, neither the commercial solver nor cuPDLP reached their maximum efficiency. Therefore, in this report, we have re-implemented and optimized cuPDLP in C language. Utilizing state-of-the-art CPU and GPU hardware, we extensively compare cuPDLP with the best commercial solvers. The experiments further highlight its substantial computational advantages and potential for solving large-scale linear programming problems. We also discuss the profound impact this breakthrough may have on mathematical programming research and the entire operations research community.Comment: fix typos, update numerical result

An Enhanced ADMM-based Interior Point Method for Linear and Conic Optimization

The ADMM-based interior point (ABIP, Lin et al. 2021) method is a hybrid algorithm that effectively combines interior point method (IPM) and first-order methods to achieve a performance boost in large-scale linear optimization. Different from traditional IPM that relies on computationally intensive Newton steps, the ABIP method applies the alternating direction method of multipliers (ADMM) to approximately solve the barrier penalized problem. However, similar to other first-order methods, this technique remains sensitive to condition number and inverse precision. In this paper, we provide an enhanced ABIP method with multiple improvements. Firstly, we develop an ABIP method to solve the general linear conic optimization and establish the associated iteration complexity. Secondly, inspired by some existing methods, we develop different implementation strategies for ABIP method, which substantially improve its performance in linear optimization. Finally, we conduct extensive numerical experiments in both synthetic and real-world datasets to demonstrate the empirical advantage of our developments. In particular, the enhanced ABIP method achieves a 5.8x reduction in the geometric mean of run time on $105$ selected LP instances from Netlib, and it exhibits advantages in certain structured problems such as SVM and PageRank. However, the enhanced ABIP method still falls behind commercial solvers in many benchmarks, especially when high accuracy is desired. We posit that it can serve as a complementary tool alongside well-established solvers

Trait anxiety is associated with reduced reward-related replay at rest

Understanding how we learn about the value and structure of our environment is central to neurocognitive theories of many psychiatric and neurological disorders. Learning processes have been extensively studied during performance of behavioural tasks (online learning) but less so in relation to resting (offline) states. A candidate mechanism for such offline learning is replay, the sequential neural reactivation of past experiences. Notably, value-based learning is especially tied to replay unfolding in reverse order relative to the original experience (backward replay). Here, we demonstrate the utility of EEG-based neural decoding for investigating offline learning, and relate it to trait anxiety, measured using the Spielberger Trait Anxiety Inventory. Participants were first required to infer sequential relationships among task objects by using a learned rule to reorganise their visual experiences into distinct sequences. Afterwards, they observed that the final object in one of the sequences was associated with a monetary reward and then entered a post-value resting state. During this rest, we find evidence of backward replay for reward-linked object sequences. The strength of such replay is negatively associated with trait anxiety and positively predicts an increased behavioural preference for reward-predictive stimuli. We also find that healthy individuals with high trait anxiety (score ≥ 45) show inefficient credit assignment irrespective of reward magnitude, indicating that this effect does not merely reflect reduced reward sensitivity. Together, these findings suggest a potential aberrant replay mechanism during offline learning in individuals with high trait anxiety. More broadly, our approach illustrates the potential of EEG for measuring structured neural representations in vivo

Effectiveness and safety of vedolizumab for ulcerative colitis: a single-center retrospective real-world study in China

Introduction: The effectiveness and safety of vedolizumab (VDZ) against ulcerative colitis (UC) have been validated in several randomized controlled trials and real-world studies in Western countries. However, there are few studies on VDZ in Asia, and the follow-up period for these studies is generally short. Therefore, this study evaluates the long-term effectiveness and safety of VDZ in Chinese patients with UC.Methods: This retrospective study included patients with moderate to severe UC treated with VDZ between September 2019 and April 2022 at Sir Run Run Shaw Hospital, College of Medicine Zhejiang University. Clinical response and remission were assessed using the patient reported outcomes and the partial Mayo Score, and mucosal remission and healing were assessed using the Mayo Endoscopy Score. The primary endpoint was defined as clinical remission at week 14, and secondary endpoints included clinical response and steroid-free clinical remission at week 14, clinical response, clinical remission, and steroid-free clinical remission at week 52, and mucosal remission and healing at weeks 14 ± 8 and 52 ± 8.Results: Overall, 64 patients with moderate to severe UC were enrolled. The clinical response, clinical remission, and steroid-free clinical remission rates at week 14 were 73.4% (47/64), 65.6% (42/64), and 54.7% (35/64), respectively. Mucosal remission and healing rates at week 14 ± 8 were 64.7% (22/34) and 38.2% (13/34), respectively. A total of 48 patients were treated with VDZ for 52 weeks. Based on intention-to-treat analysis, the clinical response, clinical remission, and steroid-free clinical remission rates at week 52 were 68.8% (44/64), 64.1% (41/64), and 64.1% (41/64), respectively. Mucosal remission and healing rates at week 52 ± 8 were 70.6% (12/17) and 35.3% (6/17), respectively. During the follow-up period, the most common adverse event was skin rash (6/64). No cases of acute infusion reactions, delayed allergic reactions, new hepatitis B infections, active tuberculosis, or malignant tumors were reported.Conclusion: In this single-center retrospective real-world study, the effectiveness of long-term use of VDZ for Chinese patients with UC was similar to the outcomes previously reported in other geographical regions and populations; no new safety signals were found compared with other registered studies

BZINB Model-Based Pathway Analysis and Module Identification Facilitates Integration of Microbiome and Metabolome Data

Integration of multi-omics data is a challenging but necessary step to advance our understanding of the biology underlying human health and disease processes. To date, investigations seeking to integrate multi-omics (e.g., microbiome and metabolome) employ simple correlation-based network analyses; however, these methods are not always well-suited for microbiome analyses because they do not accommodate the excess zeros typically present in these data. In this paper, we introduce a bivariate zero-inflated negative binomial (BZINB) model-based network and module analysis method that addresses this limitation and improves microbiome–metabolome correlation-based model fitting by accommodating excess zeros. We use real and simulated data based on a multi-omics study of childhood oral health (ZOE 2.0; investigating early childhood dental caries, ECC) and find that the accuracy of the BZINB model-based correlation method is superior compared to Spearman’s rank and Pearson correlations in terms of approximating the underlying relationships between microbial taxa and metabolites. The new method, BZINB-iMMPath, facilitates the construction of metabolite–species and species–species correlation networks using BZINB and identifies modules of (i.e., correlated) species by combining BZINB and similarity-based clustering. Perturbations in correlation networks and modules can be efficiently tested between groups (i.e., healthy and diseased study participants). Upon application of the new method in the ZOE 2.0 study microbiome–metabolome data, we identify that several biologically-relevant correlations of ECC-associated microbial taxa with carbohydrate metabolites differ between healthy and dental caries-affected participants. In sum, we find that the BZINB model is a useful alternative to Spearman or Pearson correlations for estimating the underlying correlation of zero-inflated bivariate count data and thus is suitable for integrative analyses of multi-omics data such as those encountered in microbiome and metabolome studies

Analyses of a chromosome-scale genome assembly reveal the origin and evolution of cultivated chrysanthemum

DATA AVAILABILITY : The raw sequencing data generated in this study have been deposited in the NCBI under accession PRJNA796762 and PRJNA895586 The chloroplast andmitochondrial genome were also available at GenBank under the accession number OP104251 and OP104742 respectively. The assembled genome sequences and annotations are available at Figshare [https://doi.org/10.6084/m9.figshare.21655364.v2]. The Arabidopsis ABCE and chrysanthemum CYC2 genes were used as query sequences for gene family identification, which are available at Figshare [https://doi.org/10.6084/m9.figshare.21610305]. Source data are provided with this paper.Chrysanthemum (Chrysanthemum morifolium Ramat.) is a globally important ornamental plant with great economic, cultural, and symbolic value. However, research on chrysanthemum is challenging due to its complex genetic background. Here, we report a near-complete assembly and annotation for C. morifolium comprising 27 pseudochromosomes (8.15 Gb; scaffold N50 of 303.69Mb). Comparative and evolutionary analyses reveal a whole-genome triplication (WGT) event shared by Chrysanthemum species approximately 6 million years ago (Mya) and the possible lineage-specific polyploidization of C. morifolium approximately 3 Mya. Multilevel evidence suggests that C. morifolium is likely a segmental allopolyploid. Furthermore, a combination of genomics and transcriptomics approaches demonstrate the C. morifolium genome can be used to identify genes underlying key ornamental traits. Phylogenetic analysis of CmCCD4a traces the flower colour breeding history of cultivated chrysanthemum. Genomic resources generated from this study could help to accelerate chrysanthemum genetic improvement.The National Natural Science Foundation of China, the Natural Science Fund of Jiangsu Province, China Agriculture Research System, the National Key Research and Development Program of China, the “JBGS” Project of Seed Industry Revitalisation in Jiangsu Province, the European Union’s Horizon 2020 research and innovation program from European Research Council, the Methusalem funding from Ghent University, and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institution.https://www.nature.com/ncomms/am2024BiochemistryGeneticsMicrobiology and Plant PathologySDG-15:Life on lan

Quantum simulation of Maxwell’s equations

We present quantum algorithms for electromagnetic fields governed by Maxwell’s equations. The algorithms are based on the Schrödingerisation approach, which transforms any linear PDEs and ODEs with non-unitary dynamics into a system evolving under unitary dynamics, via a warped phase transformation that maps the equation into one higher dimension. In this paper, our quantum algorithms are based on either a direct approximation of Maxwell’s equations combined with Yee’s algorithm, or a matrix representation in terms of Riemann–Silberstein vectors combined with a spectral approach and an upwind scheme. We implement these algorithms with physical boundary conditions, including perfect conductor and impedance boundaries. We also solve Maxwell’s equations for a linear inhomogeneous medium, specifically the interface problem. Several numerical experiments are performed to demonstrate the validity of this approach. In addition, instead of qubits, the quantum algorithms can also be formulated in the continuous variable quantum framework, which allows the quantum simulation of Maxwell’s equations in analog quantum simulation

Legal Nature of The Emission Allowance in China's National Carbon Trading Scheme

Emission trading scheme is a market-based approach used worldwide to reduce greenhouse gas emission and mitigate climate change. However, the legal nature of emission allowance in the ETS is controversial and differs across countries, which brings concerns to the operation of the market and the feasibility of cross-region trading. This issue has been raised in China since its national ETS is initiated in 2017. With few relevant research available, no consensus regarding the legal nature of emission allowance has been achieved in the scheme. In our study, we try to fill this research gap by examining laws and regulations of countries or regions with enforced ETS. Through literature review and case analysis, the study summarizes the practices regarding the legal nature of emission allowances in the ETS worldwide. We also provide potential options and the criteria for Chinese policymakers when deciding the legal nature of emission allowances for China’s ETS. The study finds that the legal nature of emission allowances in the ETS worldwide can mainly fall into four categories: Property Right, Limited Property Right, Compliance instrument and Depend-on-context. Different classifications of emission allowance have different key features. For example, emission allowance as a property right encourages market participation; emission allowance as a compliance instrument provides more regulatory flexibility; emission allowance as the limited property right balances regulatory flexibility and market participation and; emission allowance that depends on context brings flexibility as well as uncertainty. To decide the legal nature of emission allowance for the scheme, the policymaker should take several factors into consideration, including the emission reduction goals, the need for flexibility, the need for market participation, and the corresponding enforcement costs. Further steps to support the decision on legal nature would be researches on the features of emission allowances as different types of property rights, as well as the relevancy between legal nature and the efficiency of carbon trading markets based on empirical data