Collider Interplay for Supersymmetry, Higgs and Dark Matter

We discuss the potential impacts on the CMSSM of future LHC runs and possible electron-positron and higher-energy proton-proton colliders, considering searches for supersymmetry via MET events, precision electroweak physics, Higgs measurements and dark matter searches. We validate and present estimates of the physics reach for exclusion or discovery of supersymmetry via MET searches at the LHC, which should cover the low-mass regions of the CMSSM parameter space favoured in a recent global analysis. As we illustrate with a low-mass benchmark point, a discovery would make possible accurate LHC measurements of sparticle masses using the MT2 variable, which could be combined with cross-section and other measurements to constrain the gluino, squark and stop masses and hence the soft supersymmetry-breaking parameters m_0, m_{1/2} and A_0 of the CMSSM. Slepton measurements at CLIC would enable m_0 and m_{1/2} to be determined with high precision. If supersymmetry is indeed discovered in the low-mass region, precision electroweak and Higgs measurements with a future circular electron-positron collider (FCC-ee, also known as TLEP) combined with LHC measurements would provide tests of the CMSSM at the loop level. If supersymmetry is not discovered at the LHC, is likely to lie somewhere along a focus-point, stop coannihilation strip or direct-channel A/H resonance funnel. We discuss the prospects for discovering supersymmetry along these strips at a future circular proton-proton collider such as FCC-hh. Illustrative benchmark points on these strips indicate that also in this case FCC-ee could provide tests of the CMSSM at the loop level.Comment: 47 pages, 26 figure

The NUHM2 after LHC Run 1

We make a frequentist analysis of the parameter space of the NUHM2, in which the soft supersymmetry (SUSY)-breaking contributions to the masses of the two Higgs multiplets, $m^2_{H_{u,d}}$, vary independently from the universal soft SUSY-breaking contributions $m^2_0$ to the masses of squarks and sleptons. Our analysis uses the MultiNest sampling algorithm with over $4 \times 10^8$ points to sample the NUHM2 parameter space. It includes the ATLAS and CMS Higgs mass measurements as well as their searches for supersymmetric jets + MET signals using the full LHC Run~1 data, the measurements of $B_s \to \mu^+ \mu^-$ by LHCb and CMS together with other B-physics observables, electroweak precision observables and the XENON100 and LUX searches for spin-independent dark matter scattering. We find that the preferred regions of the NUHM2 parameter space have negative SUSY-breaking scalar masses squared for squarks and sleptons, $m_0^2 < 0$, as well as $m^2_{H_u} < m^2_{H_d} < 0$. The tension present in the CMSSM and NUHM1 between the supersymmetric interpretation of $g_\mu - 2$ and the absence to date of SUSY at the LHC is not significantly alleviated in the NUHM2. We find that the minimum $\chi^2 = 32.5$ with 21 degrees of freedom (dof) in the NUHM2, to be compared with $\chi^2/{\rm dof} = 35.0/23$ in the CMSSM, and $\chi^2/{\rm dof} = 32.7/22$ in the NUHM1. We find that the one-dimensional likelihood functions for sparticle masses and other observables are similar to those found previously in the CMSSM and NUHM1.Comment: 20 pages latex, 13 figure

The pMSSM10 after LHC Run 1

We present a frequentist analysis of the parameter space of the pMSSM10, in which the following 10 soft SUSY-breaking parameters are specified independently at the mean scalar top mass scale Msusy = Sqrt[M_stop1 M_stop2]: the gaugino masses M_{1,2,3}, the 1st-and 2nd-generation squark masses M_squ1 = M_squ2, the third-generation squark mass M_squ3, a common slepton mass M_slep and a common trilinear mixing parameter A, the Higgs mixing parameter mu, the pseudoscalar Higgs mass M_A and tan beta. We use the MultiNest sampling algorithm with 1.2 x 10^9 points to sample the pMSSM10 parameter space. A dedicated study shows that the sensitivities to strongly-interacting SUSY masses of ATLAS and CMS searches for jets, leptons + MET signals depend only weakly on many of the other pMSSM10 parameters. With the aid of the Atom and Scorpion codes, we also implement the LHC searches for EW-interacting sparticles and light stops, so as to confront the pMSSM10 parameter space with all relevant SUSY searches. In addition, our analysis includes Higgs mass and rate measurements using the HiggsSignals code, SUSY Higgs exclusion bounds, the measurements B-physics observables, EW precision observables, the CDM density and searches for spin-independent DM scattering. We show that the pMSSM10 is able to provide a SUSY interpretation of (g-2)_mu, unlike the CMSSM, NUHM1 and NUHM2. As a result, we find (omitting Higgs rates) that the minimum chi^2/dof = 20.5/18 in the pMSSM10, corresponding to a chi^2 probability of 30.8 %, to be compared with chi^2/dof = 32.8/24 (31.1/23) (30.3/22) in the CMSSM (NUHM1) (NUHM2). We display 1-dimensional likelihood functions for SUSY masses, and show that they may be significantly lighter in the pMSSM10 than in the CMSSM, NUHM1 and NUHM2. We discuss the discovery potential of future LHC runs, e+e- colliders and direct detection experiments.Comment: 47 pages, 29 figure

Supersymmetric Dark Matter after LHC Run 1

Different mechanisms operate in various regions of the MSSM parameter space to bring the relic density of the lightest neutralino, neutralino_1, assumed here to be the LSP and thus the Dark Matter (DM) particle, into the range allowed by astrophysics and cosmology. These mechanisms include coannihilation with some nearly-degenerate next-to-lightest supersymmetric particle (NLSP) such as the lighter stau (stau_1), stop (stop_1) or chargino (chargino_1), resonant annihilation via direct-channel heavy Higgs bosons H/A, the light Higgs boson h or the Z boson, and enhanced annihilation via a larger Higgsino component of the LSP in the focus-point region. These mechanisms typically select lower-dimensional subspaces in MSSM scenarios such as the CMSSM, NUHM1, NUHM2 and pMSSM10. We analyze how future LHC and direct DM searches can complement each other in the exploration of the different DM mechanisms within these scenarios. We find that the stau_1 coannihilation regions of the CMSSM, NUHM1, NUHM2 can largely be explored at the LHC via searches for missing E_T events and long-lived charged particles, whereas their H/A funnel, focus-point and chargino_1 coannihilation regions can largely be explored by the LZ and Darwin DM direct detection experiments. We find that the dominant DM mechanism in our pMSSM10 analysis is chargino_1 coannihilation: {parts of its parameter space can be explored by the LHC, and a larger portion by future direct DM searches.Comment: 21 pages, 8 figure

Strong extinction of a far-field laser beam by a single quantum dot

Through the utilization of index-matched GaAs immersion lens techniques we demonstrate a record extinction (12%) of a far-field focused laser by a single InAs/GaAs quantum dot. This contrast level enables us to report for the first time resonant laser transmission spectroscopy on a single InAs/GaAs quantum dot without the need for phase-sensitive lock-in detection

The Importance of Audit Firm Characteristics and the Drivers of Auditor Change in UK Listed Companies

This paper explores the importance of audit firm characteristics and the factors motivating auditor change based on questionnaire responses from 210 listed UK companies (a response rate of 70%). Twenty-nine potentially desirable auditor characteristics are identified from the extant literature and their importance elicited. Exploratory factor analysis reduces these variables to eight uncorrelated underlying dimensions: reputation/quality; acceptability to third parties; value for money; ability to provide non-audit services; small audit firm; specialist industry knowledge; non-Big Six large audit firm; and geographical proximity. Insights into the nature of 'the Big Six factor' emerge. Two thirds of companies had recently considered changing auditors; the main reasons cited being audit fee level, dissatisfaction with audit quality and changes in top management. Of those companies that considered change, 73% did not actually do so, the main reasons cited being fee reduction by the incumbent and avoidance of disruption. Thus audit fee levels are both a key precipitator of change and a key factor in retaining the status quo

Evaluation and Improvement of Control Vector Iteration Procedures for Optimal Control

An alternate graphical representation of linear, time-invariant, multi-input, multi-output (MIMO) system dynamics is proposed that is highly suited for exploring the influence of closedloop system parameters. The development is based on the adjustment of a scalar forward gain multiplying a cascaded multivariable controller/plant embedded in an output feedback configuration. By tracking the closed-loop eigenvalues as explicit functions of gain, it is possible to visualize the multivariable root loci in a set of &quot;gain plots&quot; consisting of two graphs: (i) magnitude of system eigenvalues versus gain and (ii) argument (angle) of system eigenvalues versus gain. The gain plots offer an alternative perspective of the standard MIMO root locus plot by depicting unambiguously the polar coordinates of each eigenvalue in the complex plane. Two example problems demonstrate the utility of gain plots for interpreting closed-loop multivariable system behavior. Introduction Since their introduction, classical control tools have been popular for analysis and design of single-input, single-output (SISO) systems. These tools may be viewed as specialized versions of more general methods that are applicable to multiinput, multi-output (MIMO) systems. Although modern &quot;statespace&quot; control techniques (relying on dynamic models of internal structure) are generally promoted as the predominant tools for multivariable system analysis, the classical control extensions offer several advantages, including requiring only an input-output map and providing direct insight into stability, performance, and robustness of MIMO systems. The understanding generated by these graphically based methods for the analysis and design of MIMO systems is a prime motivator of this research. An early graphical method for investigating the stability of linear, time-invariant (LTI) SISO systems was developed by ference transfer function matrix ([I + G(s)] where G(s) is the open-loop system transfer function matrix, rather than just 1 + g(s) for the SISO case where g{s) is the system transfer function). Despite the complication, significant research has supported the MIMO Nyquist extension for assessment of multivariable system stability and robustness The Bode plots Although promoted as an SISO tool, Evans root locus method To aid the controls engineer in extracting more information from the multivariable Evans root locus plot, we propose a set of &quot;gain plots&quot; that provide a direct and unique window into the stability, performance, and robustness of LTI MIMO systems. A conceptual framework motivating the gain plots and a discussion of their applicability to SISO systems has been presented previously Multivariable Eigenvalue Description Basic MIMO Concepts. A LTI MIMO plant can be represented in the standard state-space form as where state vector x p is length n, input vector u is length m, and output vector y is length m. Matrices A p , B p , C p , and D p are the system matrix, the control influence matrix, the output matrix, and the feed-forward matrix, respectively, of the plant with appropriate dimensions. The plant input-output dynamics are governed by the transfer function matrix, G p (s), GpW^CplsI-ApV&apos;Bp + Vp (3) The system is embedded in the closed-loop configuration shown in Fig. 1 Ml MO closed-loop negative feedback configuration where A c , B c , C c , and D c are the controller matrices representing its internal structure, in similarity to Eqs. In the MIMO root locus plot, the migration of the eigenvalues of G*(5) in the complex plane is graphed for 0 &lt; k &lt; oo. (By equating the determinant of [I + kG p (s)G c (s)] to zero, the MIMO generalization of the SISO characteristic equation The presence of the determinant is the major challenge in generalizing the SISO root locus sketching rules to MIMO systems and complicates the root locus plot.) The closed-loop system dynamics can alternatively be cast in state-space form in terms of state vector r . The closed-loop system matrix then becomes where The eigenvalues of the closed-loop system,5 = X; = eig(A&apos;) (i = 1,2, . . . , «), may be computed numerically from Eq. (6). In the examples, the loci of the eigenvalues are calculated as k is monotonically increased from zero. High Gain Behavior. As the gain is swept from zero to infinity, the closed-loop eigenvalues trace out &quot;root loci&quot; in the complex plane. At zero gain, the poles of the closed-loop system are the open-loop eigenvalues. At infinite gain some of the eigenvalues approach finite transmission zeros, defined to be those values of s that satisfy the generalized eigenvalue problem. In the absence of pole/zero cancellation, the finite transmission zeros are the roots of the determinants of G p (s) and G c (s). Algorithms have been developed for efficient and accurate computation of transmission zeros The eigenvalues can be considered as always migrating from the open-loop poles to their matching transmission zeros MIMO Gain Plots. Just as the Bode plots embellish the information of the Nyquist diagram by exposing frequency explicitly in a set of magnitude versus frequency and angle (phase) versus frequency plots, it follows that a pair of gain plots (Kurfess and Nagurka, 1991) can enhance the standard root locus plot. As the gain-domain analog of the frequencydomain Bode plots, the gain plots explicitly depict the eigenvalue magnitude versus gain in a magnitude gain plot, and the eigenvalue angle versus gain in an angle gain plot. In similarity to the Bode plots, the magnitude gain plot employs a log-log scale whereas the angle gain plot uses a semi-log scale (with the logarithms being base 10). Although gain is selected as the variable of interest in the gain plots, it should be noted that any scalar parameter may be used in the geometric analysis, leading to the more generic idea of parametric plots. Gain plots can be drawn for both SISO and MIMO systems. In MIMO systems it is assumed that a single scalar gain amplifies all controller/plant inputs. For such systems, inspection of the magnitude and angle gain plots enables one to uniquely identify locus branches as a function of gain. As such, gain plots are a natural complement to multivariable root locus plots, where uncharacteristically confusing eigenvalue trajectories can result from being drawn in a single complex plane. Furthermore, it can be shown that the slopes of the lines in the gain plots are proportionally related to the root sensitivity function (Kurfess and Nagurka, 1992). MIMO Examples This section presents two multivariable examples. The first example introduces the concept of the gain plots and demonstrates the insight they offer by &quot;unwrapping&quot; the multivariable root locus and exposing unambiguous behavior. The second example highlights the power of the gain plots in revealing typical multivariable properties, such as high gain Butterworth patterns. Example 1: Coupled MIMO Example. The forward loop dynamics of this example are given by the transfer function matrix (Equation The gain plots presented in The gain plots highlight several other important features. For example, they show that the gains corresponding to the complex conjugate eigenvalue pairs break into the real axis and then proceed toward ± oo. Complex conjugate eigenvalues are shown as symmetric lines about either the 180 or 0 deg line with equal magnitudes. Purely real eigenvalues possess equal angles (180 or 0 deg) but distinct magnitudes. This behavior is demonstrated in The rates at which the eigenvalues increase toward infinite magnitude is seen in the magnitude gain plot of From Conclusions In typical MIMO root locus plots trajectories may be camouflaged as branches may overlap. Gain plots are promoted as a means to &quot;untangle&quot; MIMO eigenvalue trajectories. The major enhancement is the visualization of eigenvalue trajectories as an explicit function of gain, assumed here to be the same static gain applied to all error signals. The perspective presented in this note is intended to complement the many tools available to the controls engineer. In particular, for MIMO systems the gain plots provide: (/) a unique description of eigenvalues and their trajectories as a parameter, such as gain, is varied, (ii) a geometric depiction of the Riemann sheets at high gain, and (Hi) a rich educational tool for conducting parametric analyses of multivariable systems. Research efforts, currently underway, may shed additional light on gain plots for multivariable systems. In addition, work by MacFarlane and&apos;Postlethwaite (1977 and In conclusion, gain plots enrich the multivarible root locus plot in much the same way that singular value frequency plots are an alternate and extended presentation of the multivariable Nyquist diagram. Their use in conjunction with the multivariable root locus provides a valuable geometric perspective on multivariable system behavior. Acknowledgment The authors wish to thank Mr. Ssu-Kuei Wang for his help, and for his earnest enthusiasm of gain plots for studying multivariable and optimal systems

CMB Polarization B-mode Delensing with SPTpol and Herschel

We present a demonstration of delensing the observed cosmic microwave background (CMB) B-mode polarization anisotropy. This process of reducing the gravitational-lensing generated B-mode component will become increasingly important for improving searches for the B modes produced by primordial gravitational waves. In this work, we delens B-mode maps constructed from multi-frequency SPTpol observations of a 90 deg$^2$ patch of sky by subtracting a B-mode template constructed from two inputs: SPTpol E-mode maps and a lensing potential map estimated from the $\textit{Herschel}$ $500\,\mu m$ map of the CIB. We find that our delensing procedure reduces the measured B-mode power spectrum by 28% in the multipole range $300 < \ell < 2300$; this is shown to be consistent with expectations from theory and simulations and to be robust against systematics. The null hypothesis of no delensing is rejected at $6.9 \sigma$. Furthermore, we build and use a suite of realistic simulations to study the general properties of the delensing process and find that the delensing efficiency achieved in this work is limited primarily by the noise in the lensing potential map. We demonstrate the importance of including realistic experimental non-idealities in the delensing forecasts used to inform instrument and survey-strategy planning of upcoming lower-noise experiments, such as CMB-S4.Comment: 17 pages, 10 figures. Comments are welcome

Design, Construction, Operation and Performance of a Hadron Blind Detector for the PHENIX Experiment

A Hadron Blind Detector (HBD) has been developed, constructed and successfully operated within the PHENIX detector at RHIC. The HBD is a Cherenkov detector operated with pure CF4. It has a 50 cm long radiator directly coupled in a window- less configuration to a readout element consisting of a triple GEM stack, with a CsI photocathode evaporated on the top surface of the top GEM and pad readout at the bottom of the stack. This paper gives a comprehensive account of the construction, operation and in-beam performance of the detector.Comment: 51 pages, 39 Figures, submitted to Nuclear Instruments and Method