Optimizing Quantum Programs against Decoherence: Delaying Qubits into Quantum Superposition

Quantum computing technology has reached a second renaissance in the last decade. However, in the NISQ era pointed out by John Preskill in 2018, quantum noise and decoherence, which affect the accuracy and execution effect of quantum programs, cannot be ignored and corrected by the near future NISQ computers. In order to let users more easily write quantum programs, the compiler and runtime system should consider underlying quantum hardware features such as decoherence. To address the challenges posed by decoherence, in this paper, we propose and prototype QLifeReducer to minimize the qubit lifetime in the input OpenQASM program by delaying qubits into quantum superposition. QLifeReducer includes three core modules, i.e.,the parser, parallelism analyzer and transformer. It introduces the layered bundle format to express the quantum program, where a set of parallelizable quantum operations is packaged into a bundle. We evaluate quantum programs before and after transformed by QLifeReducer on both real IBM Q 5 Tenerife and the self-developed simulator. The experimental results show that QLifeReducer reduces the error rate of a quantum program when executed on IBMQ 5 Tenerife by 11%; and can reduce the longest qubit lifetime as well as average qubit lifetime by more than 20% on most quantum workloads.Comment: To appear in TASE2019 - the 13th International Symposium on Theoretical Aspects of Software Engineering (submitted on Jan 25, 2019, and this is camera-ready version

Lysophospholipid acylation modulates plasma membrane lipid organization and insulin sensitivity in skeletal muscle

Aberrant lipid metabolism promotes the development of skeletal muscle insulin resistance, but the exact identity of lipid-mediated mechanisms relevant to human obesity remains unclear. A comprehensive lipidomic analysis of primary myocytes from individuals who were insulin-sensitive and lean (LN) or insulin-resistant with obesity (OB) revealed several species of lysophospholipids (lyso-PLs) that were differentially abundant. These changes coincided with greater expression of lysophosphatidylcholine acyltransferase 3 (LPCAT3), an enzyme involved in phospholipid transacylation (Lands cycle). Strikingly, mice with skeletal muscle-specific knockout of LPCAT3 (LPCAT3-MKO) exhibited greater muscle lysophosphatidylcholine/phosphatidylcholine, concomitant with improved skeletal muscle insulin sensitivity. Conversely, skeletal muscle-specific overexpression of LPCAT3 (LPCAT3-MKI) promoted glucose intolerance. The absence of LPCAT3 reduced phospholipid packing of cellular membranes and increased plasma membrane lipid clustering, suggesting that LPCAT3 affects insulin receptor phosphorylation by modulating plasma membrane lipid organization. In conclusion, obesity accelerates the skeletal muscle Lands cycle, whose consequence might induce the disruption of plasma membrane organization that suppresses muscle insulin action

Metabolic effects of selective deletion of group VIA phospholipase A2 from macrophages or pancreatic islet beta-cells

To examine the role of group VIA phospholipase

PexRAP inhibits PRDM16-mediated thermogenic gene expression

How the nuclear receptor PPARγ regulates the development of two functionally distinct types of adipose tissue, brown and white fat, as well as the browning of white fat, remains unclear. Our previous studies suggest that PexRAP, a peroxisomal lipid synthetic enzyme, regulates PPARγ signaling and white adipogenesis. Here, we show that PexRAP is an inhibitor of brown adipocyte gene expression. PexRAP inactivation promoted adipocyte browning, increased energy expenditure, and decreased adiposity. Identification of PexRAP-interacting proteins suggests that PexRAP function extends beyond its role as a lipid synthetic enzyme. Notably, PexRAP interacts with importin-β1, a nuclear import factor, and knockdown of PexRAP in adipocytes reduced the levels of nuclear phospholipids. PexRAP also interacts with PPARγ, as well as PRDM16, a critical transcriptional regulator of thermogenesis, and disrupts the PRDM16-PPARγ complex, providing a potential mechanism for PexRAP-mediated inhibition of adipocyte browning. These results identify PexRAP as an important regulator of adipose tissue remodeling

Reinforcement learning-guided long-timescale simulation of hydrogen transport in metals

Atomic diffusion in solids is an important process in various phenomena. However, atomistic simulations of diffusion processes are confronted with the timescale problem: the accessible simulation time is usually far shorter than that of experimental interests. In this work, we developed a long-timescale method using reinforcement learning that simulates diffusion processes. As a testbed, we simulate hydrogen diffusion in pure metals and a medium entropy alloy, CrCoNi, getting hydrogen diffusivity reasonably consistent with previous experiments. We also demonstrate that our method can accelerate the sampling of low-energy configurations compared to the Metropolis-Hastings algorithm using hydrogen migration to copper (111) surface sites as an example

Modeling Occupant Window Behavior in Hospitals—A Case Study in a Maternity Hospital in Beijing, China

Nowadays, relevant data collected from hospital buildings remain insufficient because hospital buildings often have stricter environmental requirements resulting in more limited data access than other building types. Additionally, existing window-opening behavior models were mostly developed and validated using data measured from the experimental building itself. Hence, their accuracy is only assessed by the algorithm’s evaluation index, which limits the model’s applicability, given that it is not tested by the actual cases nor cross-verified with other buildings. Based on the aforementioned issues, this study analyzes the window-opening behavior of doctors and patients in spring in a maternity hospital in Beijing and develops behavioral models using logistic regression. The results show that the room often has opened windows in spring when the outdoor temperature exceeds 20 °C. Moreover, the ward windows’ use frequency is more than 10 times higher than those of doctors’ office. The window-opening behavior in wards is more susceptible to the influence of outdoor temperature, while in the doctors’ office, more attention is paid to indoor air quality. Finally, by embedding the logistic regression model of each room into the EnergyPlus software to simulate the CO2 concentration of the room, it was found that the model has better applicability than the fixed schedule model. However, by performing cross-validation with different building types, it was found that, due to the particularity of doctors’ offices, the models developed for other building types cannot accurately reproduce the window-opening behavior of doctors. Therefore, more data are still needed to better understand window usage in hospital buildings and support the future building performance simulations of hospital buildings

Muscle lipogenesis balances insulin sensitivity and strength through calcium signaling

Exogenous dietary fat can induce obesity and promote diabetes, but endogenous fat production is not thought to affect skeletal muscle insulin resistance, an antecedent of metabolic disease. Unexpectedly, the lipogenic enzyme fatty acid synthase (FAS) was increased in the skeletal muscle of mice with diet-induced obesity and insulin resistance. Skeletal muscle–specific inactivation of FAS protected mice from insulin resistance without altering adiposity, specific inflammatory mediators of insulin signaling, or skeletal muscle levels of diacylglycerol or ceramide. Increased insulin sensitivity despite high-fat feeding was driven by activation of AMPK without affecting AMP content or the AMP/ATP ratio in resting skeletal muscle. AMPK was induced by elevated cytosolic calcium caused by impaired sarco/endoplasmic reticulum calcium ATPase (SERCA) activity due to altered phospholipid composition of the sarcoplasmic reticulum (SR), but came at the expense of decreased muscle strength. Thus, inhibition of skeletal muscle FAS prevents obesity-associated diabetes in mice, but also causes muscle weakness, which suggests that mammals have retained the capacity for lipogenesis in muscle to preserve physical performance in the setting of disrupted metabolic homeostasis

Relative increases in CH4 and CO2 emissions from wetlands under global warming dependent on soil carbon substrates

15 páginas.- 3 figuras.- 57 referencias.- Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41561-023-01345-6Compelling evidence has shown that wetland methane emissions are more temperature dependent than carbon dioxide emissions across diverse hydrologic conditions. However, the availability of carbon substrates, which ultimately determines microbial carbon metabolism, has not been adequately accounted for. By combining a global database and a continental-scale experimental study, we showed that differences in the temperature dependence of global wetland methane and carbon dioxide emissions (EM/C) were dependent on soil carbon-to-nitrogen stoichiometry. This can be explained mainly by the positive relationship between soil organic matter decomposability and EM/C. Our study indicates that only 23% of global wetlands will decrease methane relative to carbon dioxide emissions under future warming scenarios when soil organic matter decomposability is considered. Our findings highlight the importance of incorporating soil organic matter biodegradability into model predictions of wetland carbon–climate feedback.The authors received funding from Strategic Priority Research Program of the Chinese Academy of Sciences (XDA28030102 to Y.L.), National Natural Scientific Foundation of China (92251305 to M.N., 41622104 to Y.L.), Innovation Program of the Institute of Soil Science (ISSASIP2201 to Y.L.) and Youth Innovation Promotion Association of the Chinese Academy of Sciences (2016284 to Y.L.).Peer reviewe

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

The rapid development of open-source large language models (LLMs) has been truly remarkable. However, the scaling law described in previous literature presents varying conclusions, which casts a dark cloud over scaling LLMs. We delve into the study of scaling laws and present our distinctive findings that facilitate scaling of large scale models in two commonly used open-source configurations, 7B and 67B. Guided by the scaling laws, we introduce DeepSeek LLM, a project dedicated to advancing open-source language models with a long-term perspective. To support the pre-training phase, we have developed a dataset that currently consists of 2 trillion tokens and is continuously expanding. We further conduct supervised fine-tuning (SFT) and Direct Preference Optimization (DPO) on DeepSeek LLM Base models, resulting in the creation of DeepSeek Chat models. Our evaluation results demonstrate that DeepSeek LLM 67B surpasses LLaMA-2 70B on various benchmarks, particularly in the domains of code, mathematics, and reasoning. Furthermore, open-ended evaluations reveal that DeepSeek LLM 67B Chat exhibits superior performance compared to GPT-3.5