D. Berry

We will present a program to establish the first development and manufacturing of HEP-specific sensors monolithically integrated into a standard CMOS process using a US-based foundry. In collaboration with several US universities the project aims to develop Monolithic Active Pixel Sensors (MAPS) designs implemented in the 90 nm technology node, including simple test structures and multi-pixel arrays, and monolithic CMOS sensors with readout integrated circuits, perform detailed characterization of the detector prototypes and quantify their performance for HEP applications.

High granularity silicon pixel sensors are at the heart of energy frontier particle physics collider experiments. At an collision rate of 40\,MHz, these detectors create massive amounts of data. Signal processing that handles data incoming at those rate and intelligently reduces the data within the pixelated region of the detector \textit{at rate} will enhance physics performance and enable physics analyses that are not currently possible. Using the shape of charge clusters deposited in an array of small pixels, the physical properties of the traversing particle can be extracted with locally customized neural networks. In this first work, we present a neural network that can be embedded into the on-sensor readout and filter out hits from low momentum tracks, reducing the detector's data volume by 54.4-75.4\%. The network is designed and simulated as a custom readout integrated circuit with 28\,nm CMOS technology and is expected to operate at less than 300\,$\mu W$ with an area of less than 0.2\,mm$^2$.

The performance of electromagnetic calorimeter modules made of proton-irradiated PbWO4 crystals has been studied in beam tests. The modules, similar to those used in the Endcaps of the CMS electromagnetic calorimeter (ECAL), were formed from 5×5 matrices of PbWO4 crystals, which had previously been exposed to 24 GeV protons up to integrated fluences between 2.1× 1013 and 1.3× 1014 cm−2. These correspond to the predicted charged-hadron fluences in the ECAL Endcaps at pseudorapidity η = 2.6 after about 500 fb−1 and 3000 fb−1 respectively, corresponding to the end of the LHC and High Luminosity LHC operation periods. The irradiated crystals have a lower light transmission for wavelengths corresponding to the scintillation light, and a correspondingly reduced light output. A comparison with four crystals irradiated in situ in CMS showed no significant rate dependence of hadron-induced damage. A degradation of the energy resolution and a non-linear response to electron showers are observed in damaged crystals. Direct measurements of the light output from the crystals show the amplitude decreasing and pulse becoming faster as the fluence increases. The latter is interpreted, through comparison with simulation, as a side-effect of the degradation in light transmission. The experimental results obtained can be used to estimate the long term performance of the CMS ECAL.

We have established that the GABAA receptor alpha 6 (Gabra6) and alpha 1 (Gabra 1) subunit genes are tightly linked on mouse chromosome 11 by analysing the strain distribution patterns of RFLPs for the two genes and microsatellite markers flanking these genes in 26 BXD recombinant inbred strains. These results further demonstrate clustering of the GABAA receptor subunit genes on mouse chromosomes and the synteny for these clusters between the mouse and human genomes.

Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced, leading to unprecedented data rates exceeding those foreseen at the High Luminosity Large Hadron Collider. Signal processing that handles data incoming at a rate of O(40MHz) and intelligently reduces the data within the pixelated region of the detector at rate will enhance physics performance at high luminosity and enable physics analyses that are not currently possible. Using the shape of charge clusters deposited in an array of small pixels, the physical properties of the traversing particle can be extracted with locally customized neural networks. In this first demonstration, we present a neural network that can be embedded into the on-sensor readout and filter out hits from low momentum tracks, reducing the detector's data volume by 54.4-75.4%. The network is designed and simulated as a custom readout integrated circuit with 28 nm CMOS technology and is expected to operate at less than 300 $\mu W$ with an area of less than 0.2 mm$^2$. The temporal development of charge clusters is investigated to demonstrate possible future performance gains, and there is also a discussion of future algorithmic and technological improvements that could enhance efficiency, data reduction, and power per area.

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the charged particle passing through from pixel-cluster properties. This detector technology immediately improves the situation for offline tracking, but any major improvements in physics reach are unrealized since they are dominated by lowest-level hardware trigger acceptance. We will demonstrate track angle and hit position prediction, including errors, using a mixture density network within a single layer of silicon as well as the progress towards and status of implementing the neural network in hardware on both FPGAs and ASICs.

A search for the standard model Higgs boson decaying to two photons will be presented. The analysis will cover 5.1 fb-1 and 19.6 fb-1 of LHC proton-proton collisions collected at a center of mass energy of 7 and 8 TeV, respectively, with the CMS detector. The search reveals an excess of events near 125 GeV that is consistent with the standard model Higgs boson. The significance of the excess is 3.2σ at 125 GeV, where 4.1σ is expected. The best-fit cross-section is 0.78+0.28-0.26 times the standard model, and the best-fit mass is 125.4?0.5(stat.)?0.6(syst.) GeV. The excess is also present in a cut-based cross-check analysis with a significance of 3.9σ, where 3.5σ is expected, which corresponds to a best-fit cross-section of 1.11+0.32-0.30 at 124.5 GeV. Both the measured cross-section and couplings are consistent with a standard model Higgs boson.

In September, 1996, following the completion of an extensive Environmental Impact Statement (EIS), a record of decision (ROD) was issued by DOE selecting Sandia as the facility to take on the {sup 99}Mo production mission. {sup 99}Mo is the precursor to {sup 99m}Tc which is used in 36,000 medical procedures per day in the US. to meet US {sup 99}Mo medical demands, 20 kCi of {sup 99}Mo must be delivered to the pharmaceutical companies each week. This could be accomplished by the processing of twenty-five targets (total fission product of 15 kCi/target) each week within the SNL Hot Cell Facility (HCF). To accomplish this new mission, significant modifications to the HCF will have to be undertaken. This paper presents a brief history of the HCF, and describes modifications necessary to achieve DOE directives.