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GroundBIRD is a ground-based cosmic microwave background (CMB) experiment for observing the polarization pattern imprinted on large angular scales ($\ell > 6$ ) from the Teide Observatory in Tenerife, Spain. Our primary scientific objective is a precise measurement of the optical depth $\tau$ ($\sigma(\tau) \sim 0.01$) to the reionization epoch of the Universe to cross-check systematic effects in the measurements made by previous experiments. GroundBIRD observes a wide sky area in the Northern Hemisphere ($\sim 40\%$ of the full sky) while continuously rotating the telescope at a high speed of up to 20 rotations per minute (rpm) to overcome the fluctuations of atmospheric radiation. We have adopted the NbTiN/Al hybrid microwave kinetic inductance detectors (MKIDs) as focal plane detectors. We observe two frequency bands centered at 145 GHz and 220 GHz. The 145 GHz band picks up the peak frequency of the CMB spectrum. The 220 GHz band helps accurate removal of the contamination of thermal emission from the Galactic interstellar dust. The MKID arrays (138 MKIDs for 145GHz and 23 MKIDs for 220GHz) were designed and optimized so as to minimize the contamination of the two-level-system noise and maximize the sensitivity. The MKID arrays were successfully installed in May 2023 after the performance verification tests were performed at a laboratory. GroundBIRD has been upgraded to use the full MKID arrays, and scientific observations are now underway. The telescope is automated, so that all observations are performed remotely. Initial validations, including polarization response tests and observations of Jupiter and the moon, have been completed successfully. We are now running scientific observations., Comment: Event: SPIE Astronomical Telescopes + Instrumentation, 2024, Yokohama, Japan; paper number 13102-7, Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy XII

Many superconducting on-chip filter-banks suffer from poor coupling to the detectors behind each filter. This is a problem intrinsic to the commonly used half wavelength filter, which has a maximum theoretical coupling of 50 %. In this paper we introduce a phase coherent filter, called a directional filter, which has a theoretical coupling of 100 %. In order to to study and compare different types of filter-banks, we first analyze the measured filter frequency scatter, losses, and spectral resolution of a DESHIMA 2.0 filter-bank chip. Based on measured fabrication tolerances and losses, we adapt the input parameters for our circuit simulations, quantitatively reproducing the measurements. We find that the frequency scatter is caused by nanometer-scale line-width variations and that variances in the spectral resolution is caused by losses in the dielectric only. Finally, we include these realistic parameters in a full filter-bank model and simulate a wide range of spectral resolutions and oversampling values. For all cases the directional filter-bank has significantly higher coupling to the detectors than the half-wave resonator filter-bank. The directional filter eliminates the need to use oversampling as a method to improve the total efficiency, instead capturing nearly all the power remaining after dielectric losses., Comment: 11 pages, 4 figures. Accepted for publication by JLTP

We report measurements characterizing the performance of a kinetic inductance detector array designed for a wavelength of 25 microns and very low optical background level suitable for applications such as a far-infrared instrument on a cryogenically cooled space telescope. In a pulse counting mode of operation at low optical flux, the detectors can resolve individual 25-micron photons. In an integrating mode, the detectors remain photon noise limited over more than six orders of magnitude in absorbed power from 70 zW to 200 fW, with a limiting NEP of 4.6 x 10^-20 W/rtHz at 1 Hz. In addition, the detectors are highly stable with flat power spectra under optical load down to 1 mHz. Operational parameters of the detector are determined including the efficiency of conversion of the incident optical power into quasiparticles in the aluminum absorbing element and the quasiparticle self-recombination constant., Comment: 35 pages, 18 figures

We present a pedagogical treatment of the electroweak Higgs mechanism based solely on Feynman diagrams and S-matrix elements, without recourse to (gauge) symmetry arguments. Throughout, the emphasis is on Feynman rules and the Schwinger-Dyson equations; it is pointed out that particular care is needed in the treatment of tadpole diagrams and their symmetry factors., Comment: 35 pages

The development of new materials typically involves a process of trial and error, guided by insights from past experimental and theoretical findings. The inverse design approach for soft-matter systems has the potential to optimize specific physical parameters such as particle interactions, particle shape, or composition and packing fraction. This optimization aims to facilitate the spontaneous formation of specific target structures through self-assembly. In this study, we expand upon a recently introduced inverse design protocol for monodisperse systems to identify the required conditions and interactions for assembling crystal and quasicrystal phases within a binary mixture of two distinct species. This method utilizes an evolutionary algorithm to identify the optimal state point and interaction parameters, enabling the self-assembly of the desired structure. Additionally, we employ a convolutional neural network (CNN) that classifies different phases based on their diffraction patterns, serving as a fitness function for the desired structure. Using our protocol, we successfully inverse design two-dimensional crystalline structures, including a hexagonal lattice, and a dodecagonal quasicrystal, within a non-additive binary mixture of hard disks. Finally, we introduce a symmetry-based order parameter that leverages the encoded symmetry within the diffraction pattern. This order parameter circumvents the need for training a CNN, and is used as a fitness function to inverse design an octagonal quasicrystal., Comment: 12 pages, 5 figures

A uniform solidification front undergoes non-trivial deformations when encountering an insoluble dispersed particle in a melt. For solid particles, the overall deformation characteristics are primarily dictated by heat transfer between the particle and the surroundings, remaining unaffected by the rate of approach of the solidification front. In this Letter, we show that, conversely, when interacting with a droplet or a bubble, the deformation behaviour exhibits entirely different and unexpected behaviour. It arises from an interfacial dynamics which is specific to particles with free interfaces, namely thermal Marangoni forces. Our study employs a combination of experiments, theory, and numerical simulations to investigate the interaction between the droplet and the freezing front and unveils its surprising behaviour. In particular, we quantitatively understand the dependence of the front deformation $\Delta$ on the front propagation velocity, which, for large front velocities, can even revert from attraction ($\Delta < 0$) to repulsion ($\Delta > 0$).

Water usually contains dissolved gases, and because freezing is a purifying process these gases must be expelled for ice to form. Bubbles appear at the freezing front and are trapped in ice, making pores. These pores come in a range of sizes from microns to millimeters and their shapes are peculiar; never spherical but elongated, and usually fore-aft asymmetric. We show that these remarkable shapes result of a delicate balance between freezing, capillarity, and mass diffusion. A non-linear ordinary differential equation suffices to describe the bubbles, with only two non-dimensional parameters representing the supersaturation and the freezing rate. Our experiments provide us with a large variety of pictures of bubble shapes. We show that all of them have their rounded tip well described by an asymptotic regime of the differential equation, and that most of them can have their full shape quantitatively matched by a full solution. This enables the measurement of the freezing conditions of ice samples, and the design of freeze-cast porous materials. Furthermore, the equation exhibits a bifurcation that explains why some bubbles grow indefinitely and make long cylindrical ``ice worms'', well known to glaciologists., Comment: 14 pages, 9 figures

In this paper we examine the effect of adding CP-violating phases to the pMSSM on the Dark-Matter (DM) direct-detection cross sections, the velocity-weighted annihilation cross section, and the DM relic density. We show that $\varphi_{M_2}$ and $\varphi_{\mu}$, the phases of the wino and higgsino mass parameters, are sufficiently constrained by electron electric-dipole-moment (EDM) measurements such that the allowed values of these phases are too small to influence these DM observables. Conversely, the phase of the bino-mass parameter $\varphi_{M_1}$ and the phases associated with the trilinear couplings, $\varphi_{A^t}$, $\varphi_{A^b}$, and $\varphi_{A^\tau}$, are barely constrained by EDM experiments. We find that these cpMSSM phases can have an important impact on the mentioned DM observables. This especially concerns pMSSM points that lie on the boundary of exclusion, as observables can be affected by cpMSSM phases to the extent that they are either pushed into the observable region, or outside the excluded region., Comment: 24 pages, 10 figures

Frozen water might appear opaque since gas bubbles can get trapped in the ice during the freezing process. They nucleate and then grow near the advancing solidification front, due to the formation of a gas supersaturation region in its vicinity. A delicate interplay between the rate of mass transfer and the rate of freezing dictates the final shapes and sizes of the entrapped gas bubbles. In this work, we experimentally and numerically investigate the initial growth of such gas bubbles that nucleate and grow near the advancing ice front. We show that the initial growth of these bubbles is governed by diffusion and is enhanced due to a combination of the presence of the background gas concentration gradient and the motion of the approaching front. Additionally, we recast the problem into that of mass transfer to a moving spherical object in a homogeneous concentration field, finding good agreement between our experimental data and the existing scaling relations for that latter problem. Lastly, we address how fluid flow around the bubble might further affect this growth and qualitatively explore this through numerical simulations., Comment: 19 pages, 10 figures

The multicomponent coagulation equation is a generalisation of the Smoluchowski coagulation equation in which size of a particle is described by a vector. As with the original Smoluchowski equation, the multicomponent coagulation equation features gelation when supplied with a multiplicative kernel. Additionally, a new type of behaviour called localization is observed due to the multivariate nature of the particle size distribution. Here we extend and apply the branching process representation technique, which we introduced to study differential equations in our previous work, to find a concise probabilistic solution of the multicomponent coagulation equation supplied with monodisperse initial conditions and provide short proofs for the gelation time and localization., Comment: 12 pages

Solidification of complex liquids is pertinent to numerous natural and industrial processes. Here, we examine the freezing of a W/O/W double-emulsion, i.e., water-in-oil compound droplets dispersed in water. We show that the solidification of such hierarchical emulsions can trigger a topological transition; for example, in our case, we observe the transition from the stable W/O/W state to a (frozen) O/W single-emulsion configuration. Strikingly, this transition is characterised by sudden expulsion of the inner water drop from the encapsulating oil droplet. We propose that this topological transition is triggered by the freezing of the encapsulating oil droplet from the outside in, putting tension on the inner water drop thus, destabilizing the W/O/W configuration. Using high-speed imaging we characterize the destabilization process. Interestingly, we find that below a critical size of the inner drop, $R_{\mathrm{in,crit}} \approx 19 \, \mu\mathrm{m}$, the topological transition does not occur any more and the double-emulsion remains stable, in line with our interpretation., Comment: 10 pages, 7 figures

Particles at liquid interfaces have the tendency to cluster due to capillary forces competing to gravitational buoyancy (i.e., normal to the distorted free surface). This is known as the Cheerios effect. Here we experimentally and theoretically study the interaction between two submerged particles near an advancing water-ice interface during the freezing process. Particles that are thermally more conductive than water are observed to attract each other and form clusters once frozen. We call this feature the frozen Cheerios effect, where interactions are driven by alterations to the direction of the experienced repelling force (i.e., normal to the distorted isotherm). On the other hand, particles less conductive than water separate, highlighting the importance of thermal conduction during freezing. Based on existing models for single particle trapping in ice, we develop an understanding of multiple particle interaction. We find that the overall efficacy of the particle-particle interaction critically depends on the solidification front velocity. Our theory explains why the thermal conductivity mismatch between the particles and water dictates the attractive/repulsive nature of the particle-particle interaction., Comment: 15 pages, 10 figures

The PRobe far-Infrared Mission for Astrophysics (PRIMA) is under study as a potential far-IR space mission, featuring actively cooled optics, and both imaging and spectroscopic instrumentation. To fully take advantage of the low background afforded by a cold telescope, spectroscopy with PRIMA requires detectors with a noise equivalent power (NEP) better than $1 \times 10^{-19}$ W Hz$^{-1/2}$. To meet this goal we are developing large format arrays of kinetic inductance detectors (KIDs) to work across the $25-250$ micron range. Here we present the design and characterization of a single pixel prototype detector optimized for $210$ micron. The KID consists of a lens-coupled aluminum inductor-absorber connected to a niobium interdigitated capacitor to form a 2 GHz resonator. We have fabricated a small array with 28 KIDs, and we measure the performance of one of these detectors with an optical loading in the $0.01 - 300$ aW range. At low loading the detector achieves an NEP of $9\times10^{-20}$ W Hz$^{-1/2}$ at a 10 Hz readout frequency, and the lens-absorber system achieves a good optical efficiency. An extrapolation of these measurements suggest this detector may remain photon noise limited at up to 20 fW of loading, offering a high dynamic range for PRIMA observations of bright astronomical sources., Comment: revised submission to IEEE Transactions on Terahertz Science and Technology

Far-infrared (far-IR) astrophysics missions featuring actively cooled telescopes will offer orders of magnitude observing speed improvement at wavelengths where galaxies and forming planetary systems emit most of their light. The PRobe far-Infrared Mission for Astrophysics (PRIMA), which is currently under study, emphasizes low and moderate resolution spectroscopy throughout the far-IR. Full utilization of PRIMA's cold telescope requires far-IR detector arrays with per-pixel noise equivalent powers (NEPs) at or below 1 x 10-19 W/rtHz. We are developing low-volume Aluminum kinetic inductance detector (KID) arrays to reach these sensitivities. We will present on the development of our long-wavelength (210 um) array approach, with a focus on multitone measurements of our 1,008-pixel arrays. We measure an NEP below 1 x 10-19 W/rtHz for 73 percent of our pixels., Comment: 9 pages, 5 figures, 20th International Workshop on Low Temperature Detectors, submitted to the Journal of Low Temperature Physics

Future generation of astronomical imaging spectrometers are targeting the far infrared wavelengths to close the THz astronomy gap. Similar to lens antenna coupled Microwave Kinetic Inductance Detectors (MKIDs), lens absorber coupled MKIDs are a candidate for highly sensitive large format detector arrays. However, the latter is more robust to misalignment and assembly issues at THz frequencies due to its incoherent detection mechanism while requiring a less complex fabrication process. In this work, the performance of such detectors is investigated. The fabrication and sensitivity measurement of several lens absorber coupled MKID array prototypes operating at 6.98 and 12 THz central frequencies is on-going., Comment: 2 pages, 2 figures, IRMMW-THz conference paper

The $U(1)_{L_\mu-L_\tau}$ extended Standard Model (SM) is anomaly free, and contains a massive $Z^\prime$ boson. The associated Higgs, which generates the $Z'$'s mass via spontaneous symmetry breaking (SSB) can mix with the SM Higgs. The new parameters relating to extra Higgs cannot be probed at the LHC with final states containing no more than $4$ leptons. Therefore, we use signatures with at least $6$ leptons to probe the parameter space through LHC experiments. Since SM predicts a lower cross section for a final state with at least $6$ leptons than is currently visible at the LHC, the background is negligible, thereby making this channel an extremely sensitive probe. We find that in a limited region of the parameter space this channel can strongly constrain the associated $U(1)_{L_\mu-L_\tau}$ coupling constant, even more so than for a $4$ lepton or fewer final state., Comment: 5 pages, 3 figures. Minor changes based on comments received

We show that a large class of first-order conservation PDEs can be probabilistically represented using multi-type branching processes. The representation holds when the initial conditions are linear combinations of negative exponentials. This class contains Burgers' equation in 1D, which may develop a gradient blow-up in finite time, as well as other equations with more general nonlinearities. We also show how the time of gradient blow up can be identified by studying criticality conditions of the corresponding branching processes.

In this paper, the problem of electric vehicle (EV) charging at the workplace is addressed via a two-layer predictive algorithm. We consider a time of use (TOU) pricing model for energy drawn from the grid and try to minimize the charging cost incurred by the EV charging station (EVCS) operator via an economic layer based on dynamic programming (DP) approach. An adaptive prediction algorithm based on a non-parametric stochastic model computes the projected EV load demand over the day which helps in the selection of optimal loading policy for the EVs in the economic layer. The second layer is a scheduling algorithm designed to share the allocated power limit (obtained from economic layer) among the charging EVs during each charge cycle. The modeling and validation is performed using ACN data-set from Caltech. Comparison of the proposed scheme with a conventional DP algorithm illustrates its effectiveness in terms of supplying the requested energy despite lacking user input for departure time.

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which is where the previous topics meet to explore three dimensional protein structures through computational analysis. We provide an overview of existing computational techniques, to validate, simulate, predict and analyse protein structures. More importantly, it will aim to provide practical knowledge about how and when to use such techniques. We will consider proteins from three major vantage points: Protein structure quantification, Protein structure prediction, and Protein simulation & dynamics. In this chapter we explore basic physical and chemical concepts required to understand protein folding. We introduce major (de)stabilising factors of folded protein structures such as the hydrophobic effect and backbone entropy. In addition, we consider different states along the folding pathway, as well as natively disordered proteins and aggregated protein states. In this chapter, an intuitive understanding is provided about the protein folding process, to prepare for the next chapter on the thermodynamics of protein folding. In particular, it is emphasized that protein folding is a stochastic process and that proteins unfold and refold in a dynamic equilibrium. The effect of temperature on the stability of the folded and unfolded states is also explained., Comment: editorial responsability: Juami H. M. van Gils, K. Anton Feenstra, Sanne Abeln. This chapter is part of the book "Introduction to Protein Structural Bioinformatics". The Preface arXiv:1801.09442 contains links to all the (published) chapters. The update adds available arxiv hyperlinks for the chapters

When an immiscible oil drop is immersed in a stably stratified ethanol-water mixture, the Marangoni flow on the surface of the drop can experience an oscillatory instability, so that the drop undergoes a transition from levitating to bouncing. The onset of the instability and its mechanisms have been studied previously, yet the bouncing motion of the drop itself, which is a completely different problem, has not yet been investigated. Here we study how the bouncing characteristics (jumping height, rising and sinking time) depend on the control parameters (drop radius, stratification strength, drop viscosity). We first record experimentally the bouncing trajectories of drops of different viscosities in different stratifications. Then a simplified dynamical analysis is performed to get the scaling relations of the jumping height and the rising and sinking times. The rising and sinking time scales are found to depend on the drag coefficient of the drop $C_D^S$ in the stratified liquid, which is determined empirically for the current parameter space. For low viscosity (5 cSt) oil drops the results on the drag coefficient match the ones from the literature. For high viscosity (100 cSt) oil drops the parameter space had not been explored and the drag coefficients are not readily available. Numerical simulations are therefore performed to provide external verification for the drag coefficients, which well match with the experimental results., Comment: 21 pages, 11 figures

Neutral particles capable of travelling cosmic distances from a source to detectors on Earth are limited to photons and neutrinos. Examination of the Dark Matter annihilation/decay spectra for these particles reveals the presence of continuum spectra (e.g. due to fragmentation and W or Z decay) and peaks (due to direct annihilations/decays). However, when one explores extensions of the Standard Model (BSM), unexplored spectra emerge that differ significantly from those of the Standard Model (SM) for both neutrinos and photons. In this paper, we argue for the inclusion of important spectra that include peaks as well as previously largely unexplored entities such as boxes and combinations of box, peak and continuum decay spectra., Comment: 7 pages, 2 figures

Freezing of dispersions is omnipresent in science and technology. While the passing of a freezing front over a solid particle is reasonably understood, this is not so for soft particles. Here, using an oil-in-water emulsion as a model system, we show that when engulfed into a growing ice front, a soft particle severely deforms. This deformation strongly depends on the engulfment velocity $V$, even forming pointy-tip shapes for low values of $V$. We find such singular deformations are mediated by interfacial flows in $\textit{nanometric}$ thin liquid films separating the non-solidifying dispersed droplets and the solidifying bulk. We model the fluid flow in these intervening thin films using a lubrication approximation and then relate it to the deformation sustained by the dispersed droplet., Comment: 6 pages, 5 figures

Current ethical debates on the use of artificial intelligence (AI) in health care treat AI as a product of technology in three ways: First, by assessing risks and potential benefits of currently developed AI-enabled products with ethical checklists; second, by proposing ex ante lists of ethical values seen as relevant for the design and development of assisting technology, and third, by promoting AI technology to use moral reasoning as part of the automation process. Subsequently, we propose a fourth approach to AI, namely as a methodological tool to assist ethical reflection. We provide a concept of an AI-simulation informed by three separate elements: 1) stochastic human behavior models based on behavioral data for simulating realistic settings, 2) qualitative empirical data on value statements regarding internal policy, and 3) visualization components that aid in understanding the impact of changes in these variables. The potential of this approach is to inform an interdisciplinary field about anticipated ethical challenges or ethical trade-offs in concrete settings and, hence, to spark a re-evaluation of design and implementation plans. This may be particularly useful for applications that deal with extremely complex values and behavior or with limitations on the communication resources of affected persons (e.g., persons with dementia care or for care of persons with cognitive impairment). Simulation does not replace ethical reflection but does allow for detailed, context-sensitive analysis during the design process and prior to implementation. Finally, we discuss the inherently quantitative methods of analysis afforded by stochastic simulations as well as the potential for ethical discussions and how simulations with AI can improve traditional forms of thought experiments and future-oriented technology assessment., Comment: 26 pages, 3 figures

In dark-matter annihilation channels to hadronic final states, stable particles -- such as positrons, photons, antiprotons, and antineutrinos -- are produced via complex sequences of phenomena including QED/QCD radiation, hadronisation, and hadron decays. These processes are normally modelled by Monte Carlo event generators whose limited accuracy imply intrinsic QCD uncertainties on the predictions for indirect-detection experiments like Fermi-LAT, Pamela, IceCube or AMS-02. In this article, we perform a complete analysis of QCD uncertainties in antimatter spectra from dark-matter annihilation, based on parametric variations of the Pythia 8 event generator. After performing several retunings of light-quark fragmentation functions, we define a set of variations that span a conservative estimate of the QCD uncertainties. We estimate the effects on antimatter spectra for various annihilation channels and final-state particle species, and discuss their impact on fitted values for the dark-matter mass and thermally-averaged annihilation cross section. We find dramatic impacts which can go up to $\mathcal{O}(40)$ GeV for uncertainties on the dark-matter mass and up to $\mathcal{O}(10\%)$ for the annihilation cross section. We provide the spectra in tabulated form including QCD uncertainties and code snippets to perform fast dark-matter fits, in this https://github.com/ajueid/qcd-dm.github.io.git repository., Comment: v1: 52 pages, 21 figures, and 9 tables

Unforeseen particle accelerator interruptions, also known as interlocks, lead to abrupt operational changes despite being necessary safety measures. These may result in substantial loss of beam time and perhaps even equipment damage. We propose a simple yet powerful binary classification model aiming to forecast such interruptions, in the case of the High Intensity Proton Accelerator complex at the Paul Scherrer Institut. The model is formulated as logistic regression penalized by least absolute shrinkage and selection operator, based on a statistical two sample test to distinguish between unstable and stable states of the accelerator. The primary objective for receiving alarms prior to interlocks is to allow for countermeasures and reduce beam time loss. Hence, a continuous evaluation metric is developed to measure the saved beam time in any period, given the assumption that interlocks could be circumvented by reducing the beam current. The best-performing interlock-to-stable classifier can potentially increase the beam time by around 5 min in a day. Possible instrumentation for fast adjustment of the beam current is also listed and discussed., Comment: 12 pages, 13 figures