A Ferroelectric Compute-in-Memory Annealer for Combinatorial Optimization Problems

Computationally hard combinatorial optimization problems (COPs) are ubiquitous in many applications, including logistical planning, resource allocation, chip design, drug explorations, and more. Due to their critical significance and the inability of conventional hardware in efficiently handling scaled COPs, there is a growing interest in developing computing hardware tailored specifically for COPs, including digital annealers, dynamical Ising machines, and quantum/photonic systems. However, significant hurdles still remain, such as the memory access issue, the system scalability and restricted applicability to certain types of COPs, and VLSI-incompatibility, respectively. Here, a ferroelectric field effect transistor (FeFET) based compute-in-memory (CiM) annealer is proposed. After converting COPs into quadratic unconstrained binary optimization (QUBO) formulations, a hardware-algorithm co-design is conducted, yielding an energy-efficient, versatile, and scalable hardware for COPs. To accelerate the core vector-matrix-vector (VMV) multiplication of QUBO formulations, a FeFET based CiM array is exploited, which can accelerate the intended operation in-situ due to its unique three-terminal structure. In particular, a lossless compression technique is proposed to prune typically sparse QUBO matrix to reduce hardware cost. Furthermore, a multi-epoch simulated annealing (MESA) algorithm is proposed to replace conventional simulated annealing for its faster convergence and better solution quality. The effectiveness of the proposed techniques is validated through the utilization of developed chip prototypes for successfully solving graph coloring problem, indicating great promise of FeFET CiM annealer in solving general COPs.Comment: 39 pages, 12 figure

Prevalence and Characterization of Staphylococcus aureus Isolated From Women and Children in Guangzhou, China

The prevalent Staphylococcus aureus clones and antibiotic susceptibility profiles are known to change dynamically and geographically; however, recent S. aureus strains causing infections in women and children in China have not been characterized. In this study, we analyzed the molecular epidemiology and antimicrobial resistance of S. aureus isolated from patients in four centers for women and children in Guangzhou, China. In total, 131 S. aureus isolates (100 from children and 31 from women) were analyzed by spa typing, multi-locus sequence typing, virulence gene and antimicrobial resistance profiling, staphylococcal chromosomal cassette mec typing, and mutation analyses of rpoB. A total of 58 spa types, 27 sequence types (STs), and 10 clonal complexes (CCs) were identified. While CC59 (ST59-IV, 48.8%; ST338-III, 35.7%) and CC45 (ST45-IV, 100%) were the major clones (84.4%) among MRSA isolates, CC5 (ST188, 24.3%; ST1, 21.6%) and CC398 (ST398, 70%) were the major ones (70.1%) among MSSA isolates. ST338-MRSA-III mostly found in pus but hardly in respiratory tract samples while ST45-MRSA-IV was on the opposite, even though they both found in blood and cerebrospinal fluid sample frequently. Staphylococcal enterotoxin genes seb-seq-sek were strongly associated with ST59 and ST338, while sec was associated with ST45, ST121, ST22, and ST30. All ST338, ST1232, and SCCmec III isolates carried lukF/S-PV genes. A total of 80% of ST338 isolates were resistant to erythromycin, clindamycin, and tetracycline. All ST45 isolates exhibited intermediate or complete resistance to rifampicin. In total, 481 HIS/ASN mutations in rpoB were found in rifampicin-resistant or intermediate-resistant isolates. ST338-III and ST45-IV emerged as two of three major clones in MRSA isolates from women and children in Guangzhou, China, though ST59-MRSA-IV remained the most prevalent MRSA clone. Clonal distribution of S. aureus varied, depending on the specimen source. Virulence genes and antibiograms were closely associated with the clonal lineage. These results clarified the molecular epidemiology of S. aureus from women and children in Guangzhou, China, and provide critical information for the control and treatment of S. aureus infections

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Variability-aware parametric yield estimation for analog/mixed-signal circuits : concepts, algorithms, and challenges

With technology scaling down to 90nm and below, process variation has become a primary challenge for both design and fabrication of analog/mixed-signal circuits due to significantly increased circuit failures and yield loss. As a result, it is urgently required to estimate the yield of one design efficiently in the presence of process variation. In this paper, we present the recent advance for yield estimation for analog/mixed-signal circuits with a number of critical topics and techniques discussed and classified into two categories. The first is performance domain method, which requires extensive Monte Carlo simulations; and the second is parameter domain method, which requires the characterization of yield boundary defined by performance constraints without using Monte Carlo. We review the pros and cons of these methods, which are evaluated by a number of circuit examples with quantitative comparison.Accepted versio

Study on the Propagation Laws of Hydrofractures Meeting a Faulted Structure in the Coal Seam

Hydraulic fracturing is an important technique for increasing coal seam permeability and productivity of CBM (coalbed methane). As a common type of faulted structure in the coal seam, the fault has a direct impact on the direction and scope of hydrofracture propagation, weakening fracturing effects. To study the propagation laws of a hydrofracture meeting a fault in the coal seam, based on a two-dimensional model of a hydrofracture meeting a fault, the combined elastic mechanics and fracture mechanics, the propagation mode, critical internal water pressure, and influencing factors were analyzed. A numerical simulation on the propagation laws of hydrofracture meeting a fault was conducted by using the coupling system of flow and solid in the rock failure process analysis (RFPA2D-Flow). The results show that the horizontal crustal stress difference, the intersection angle between hydrofracture and fault plane, and the physical mechanics characteristics of coal-rock bed are the main factors influencing fracture propagation. With a decrease of horizontal crustal stress differences, intersection angle and an increase of roof elasticity modulus, it is easier for the footwall hydrofracture to enter the hanging wall along the bedding plane, forming an effective fracture. When the stress difference is large and the dip angle of fault plane surpasses 45°, the hydrofracture is easy to propagate towards the coal roof and floor by going through the fault plane. At this time, the coal seams of the footwall and the hanging wall should be fractured respectively to ensure fracturing effects, and the support of the roof and floor should be strengthened. The field experiment, theoretical analysis and numerical simulation were consistent in their results, which will contribute to the optimization of hydraulic fracturing and the prediction of hydrofracture in the coal seams containing faults