The addition of O 2 to gas mixtures in time projection chambers containing CS 2 has recently been shown to produce multiple negative ions that travel at slightly different velocities. This allows a measurement of the absolute position of ionising events in the z (drift) direction. In this work, we apply the z-fiducialisation technique to a directional dark matter search. We present results from a 46.3 live-day source-free exposure of the DRIFT-IId detector run in this new mode. With full-volume fiducialisation, we have achieved the first background-free operation of a directional detector. The resulting exclusion curve for spindependent WIMP-proton interactions reaches 1.1 pb at 100 GeV/c 2 , a factor of 2 better than our previous work. We describe the automated analysis used here, and argue that detector upgrades, implemented after the acquisition of these data, will bring an additional factor of 3 improvement in the near future.arXiv:1410.7821v3 [hep-ex] 23 Jul 2015 DRIFT-IId detector and science runsThe DRIFT experiment is sited at a depth of 1.1 km in the STFC Boulby Underground Science Facility [29], which provides 2805 m.w.e. shielding against cosmic rays. The TPC is housed inside a stainless steel cubic vacuum vessel, surrounded on all sides with 44 g cm −2 of polypropylene pellets to shield against neutrons from the cavern walls. The vessel was filled with a mixture of 30:10:1 Torr CS 2 :CF 4 :O 2 gas, and sealed for the duration of each run. This departure from the normal mode of operation, in which gas is flowed at a constant rate of one complete vacuum vessel change (590 g) /d, was necessary due to safety concerns over sources of ignition in the constant flow system. These concerns have since been addressed with modifications to the gas system.The DRIFT-IId NITPC consists of a thin-film (0.9 µm aluminised Mylar), texturised central cathode [25] at a potential of -31.9 kV faced on either side by two 1 m 2 multi-wire proportional chambers (hereafter, the 'left' and 'right' MWPCs) at a distance of 50 cm. In this way, two 50-cm-long drift regions are defined. A field cage of 31 stainless steel rings on either side steps down the voltage smoothly between the central cathode and the MWPCs to ensure a uniform electric field of 580 V cm −1 throughout the drift regions. The MWPCs are made up of a central grounded anode plane of 20 µm diameter stainless steel wires with 2 mm pitch, sandwiched between two perpendicular grid planes of 100 µm wires at -2884 V, again with 2 mm pitch and separated by 1 cm from the anode plane. A full description of the detector can be found in Ref. [30].Both the inner grid and anode planes have every eighth wire joined together and read out as one, such that a single 'octave' of wires reads out 8 × 2 = 16 mm in x and y: large enough to contain the recoil events of interest. The outermost 52 (41) wires of the 512 total on the inner grid (anode) planes are grouped together into x (y) veto regions, reducing the fiducial volume of the detector to 0.80 m 3 . The anode and grid veto signal...

We present results from a 54.7 live-day shielded run of the DRIFT-IId detector, the world's most sensitive, directional, dark matter detector. Several improvements were made relative to our previous work including a lower threshold for detection, a more robust analysis and a tenfold improvement in our gamma rejection factor. After analysis, no events remain in our fiducial region leading to an exclusion curve for spindependent WIMP-proton interactions which reaches 0.28 pb at 100 GeV/c 2 , a fourfold improvement on our previous work. We also present results from a 45.4 live-day unshielded run of the DRIFT-IId detector during which 14 nuclear recoil-like events were observed. We demonstrate that the observed nuclear recoil rate of 0.31±0.08 events per day is consistent with detection of ambient, fast neutrons emanating from the walls of the Boulby Underground Science Facility.

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Given the ubiquity of lattice models in physics, it is imperative for researchers to possess robust methods for quantifying clusters on the lattice -whether they be Ising spins or clumps of molecules. Inspired by biophysical studies, we present Python code for handling clusters on a 2D periodic lattice. Properties of individual clusters, such as their area, can be obtained with a few function calls. Our code invokes an unsupervised machine learning method called hierarchical clustering, which is simultaneously effective for the present problem and simple enough for non-experts to grasp qualitatively. Moreover, our code transparently merges clusters neighboring each other across periodic boundaries using breadth-first search (BFS), an algorithm well-documented in computer science pedagogy. The fact that our code is written in Python -instead of proprietary languages -further enhances its value for reproducible science. PROGRAM SUMMARYProgram Title: Cluster Collector Licensing provisions: Creative Common by 4.0 Programming language: Python Nature of problem: Lattice simulations of, say, membrane proteins model the spatiotemporal organization of a system. In order to extract insights from such sim- ulations, we need robust methods for identifying clusters of simulated objects on the lattice. Solution method: Hierarchical clustering first identifies all potential clusters. Then, breadth-first search connects together clusters that neighbor each other across periodic boundaries.

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