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Perovskite films have rapidly emerged as leading active materials in optoelectronic devices due to their strong optical absorption, high carrier mobility and ease of fabrication. Whilst proving to be promising materials for solar cells and light-emitting diodes, another application of perovskites which makes effective use of their unique properties is sensitisation for photon upconversion. Consisting of a bulk perovskite sensitiser alongside an adjacent organic semiconductor film, the upconverting system can absorb multiple low-energy photons to emit high-energy photons. In this work, density functional theory, in conjunction with GW theory, is utilised to investigate the electronic structure at the MAPbI$_3$/rubrene interface for different surface terminations of MAPbI$_3$. From this investigation, we reveal that the surface termination of the perovskite layer greatly affects the charge density at the interface and within the rubrene layer driven by the formation of interfacial dipole layers. The formation of a strong interfacial dipole for the lead-iodide terminated perovskite alters the band alignment of the heterojunction and is expected to facilitate more efficient hole transfer. For the perovskite surface terminated with the methylammonium iodide layer, the highest occupied molecular orbital of the adjacent rubrene layer lies deep within the perovskite band gap. This termination type is further characterized by a lower density of states near the band edges thereby acting as a spacer which is anticipated to decrease the probability of charge transfer across the interface. Thus based on our results, PbI$_2$-terminated perovskite surfaces are predicted to be favourable for applications where hole transfer to a rubrene layer is ideal, highlighting the significance of surface termination for all systems where the electronic environment at the interface is crucial to performance.

While subword tokenizers such as BPE and WordPiece are typically used to build vocabularies for NLP models, the method of decoding text into a sequence of tokens from these vocabularies is often left unspecified, or ill-suited to the method in which they were constructed. We provide a controlled analysis of seven tokenizer inference methods across four different algorithms and three vocabulary sizes, performed on a novel intrinsic evaluation suite we curated for English, combining measures rooted in morphology, cognition, and information theory. We show that for the most commonly used tokenizers, greedy inference performs surprisingly well; and that SaGe, a recently-introduced contextually-informed tokenizer, outperforms all others on morphological alignment., Comment: ACL 2024 (main)

Tokenization is a foundational step in natural language processing (NLP) tasks, bridging raw text and language models. Existing tokenization approaches like Byte-Pair Encoding (BPE) originate from the field of data compression, and it has been suggested that the effectiveness of BPE stems from its ability to condense text into a relatively small number of tokens. We test the hypothesis that fewer tokens lead to better downstream performance by introducing PathPiece, a new tokenizer that segments a document's text into the minimum number of tokens for a given vocabulary. Through extensive experimentation we find this hypothesis not to be the case, casting doubt on the understanding of the reasons for effective tokenization. To examine which other factors play a role, we evaluate design decisions across all three phases of tokenization: pre-tokenization, vocabulary construction, and segmentation, offering new insights into the design of effective tokenizers. Specifically, we illustrate the importance of pre-tokenization and the benefits of using BPE to initialize vocabulary construction. We train 64 language models with varying tokenization, ranging in size from 350M to 2.4B parameters, all of which are made publicly available., Comment: EMNLP 2024

Strong gravitational lensing of quasars has the potential to unlock the poorly understood physics of these fascinating objects, as well as serve as a probe of the lensing mass distribution and of cosmological parameters. In particular, gravitational microlensing by compact bodies in the lensing galaxy can enable mapping of quasar structure to $\lt 10^{-6}$ arcsec scales. Some of this potential has been realized over the past few decades, however the upcoming era of large sky surveys promises to bring this to full fruition. Here we review the theoretical framework of this field, describe the prominent current methods for parameter inference from quasar microlensing data across different observing modalities, and discuss the constraints so far derived on the geometry and physics of quasar inner structure. We also review the application of strong lensing and microlensing to constraining the granularity of the lens potential, i.e. the contribution of the baryonic and dark matter components, and the local mass distribution in the lens, i.e. the stellar mass function. Finally, we discuss the future of the field, including the new possibilities that will be opened by the next generation of large surveys and by new analysis methods now being developed., Comment: To be submitted to Space Science Reviews, Topical Collection "Strong Gravitational Lensing", eds. J. Wambsganss et al

Singlet fission, which has applications in areas ranging form solar energy to quantum information, relies critically on transitions within a multi-spin manifold. These transitions are driven by fluctuations in the spin-spin exchange interaction, which have been linked to changes in nuclear geometry or exciton migration. Whilst simple calculations have supported this mechanism, to date little effort has been made to model realistic fluctuations which are informed by the actual structure and properties of physical materials. In this paper, we develop a modular computational pipeline for calculating singlet fission spin dynamics by way of electronic structural calculations, molecular dynamics, and numerical models of spin dynamics. The outputs of this pipeline aid in the interpretation of measured spin dynamics and allow us to place constraints on geometric fluctuations which are consistent with these observations., Comment: 23 pages (including SI), 7 Figures

The relationship linking a galaxy cluster's total mass with the concentration of its mass profile and its redshift is a fundamental prediction of the Cold Dark Matter (CDM) paradigm of cosmic structure formation. However, confronting those predictions with observations is complicated by the fact that simulated clusters are not representative of observed samples where detailed mass profile constraints are possible. In this work, we calculate the Symmetry-Peakiness-Alignment (SPA) morphology metrics for maps of X-ray emissivity from THE THREE HUNDRED project hydrodynamical simulations of galaxy clusters at four redshifts, and thereby select a sample of morphologically relaxed, simulated clusters, using observational criteria. These clusters have on average earlier formation times than the full sample, confirming that they are both morphologically and dynamically more relaxed than typical. We constrain the concentration-mass-redshift relation of both the relaxed and complete sample of simulated clusters, assuming power-law dependences on mass ($\kappa_m$) and $1+z$ ($\kappa_\zeta$), finding $\kappa_m = -0.12 \pm 0.07$ and $\kappa_\zeta = -0.27 \pm 0.19$ for the relaxed subsample. From an equivalently selected sample of massive, relaxed clusters observed with ${\it Chandra}$, we find $\kappa_m = -0.12 \pm 0.08$ and $\kappa_\zeta = -0.48 \pm 0.19$, in good agreement with the simulation predictions. The simulated and observed samples also agree well on the average concentration at a pivot mass and redshift providing further validation of the $\Lambda$CDM paradigm in the properties of the largest gravitationally collapsed structures observed. This also represents the first clear detection of decreasing concentration with redshift, a longstanding prediction of simulations, in data., Comment: 10 pages, 10 figures. Accepted by MNRAS

We implement a new observational method for mapping the aliphatic hydrocarbon content in the solid phase in our Galaxy, based on spectrophotometric imaging of the 3.4 $\mu$m absorption feature from interstellar dust. We previously demonstrated this method in a field including the Galactic Centre cluster. We applied the method to a new field in the Galactic centre where the 3.4 $\mu$m absorption feature has not been previously measured and we extended the measurements to a field in the Galactic plane to sample the diffuse local interstellar medium, where the 3.4 $\mu$m absorption feature has been previously measured. We have analysed 3.4 $\mu$m optical depth and aliphatic hydrocarbon column density maps for these fields. Optical depths are found to be reasonably uniform in each field, without large source-to-source variations. There is, however, a weak trend towards increasing optical depth in a direction towards $b=0^{\circ}$ in the Galactic centre. The mean value of column densities and abundances for aliphatic hydrocarbon were found to be about several $\rm \times 10^{18} \, cm^{-2}$ and several tens $\times 10^{-6}$, respectively for the new sightlines in the Galactic plane. We conclude that at least 10-20% of the carbon in the Galactic plane lies in aliphatic form.

Despite the long history of spectroscopic studies of the C$_2$ molecule, fundamental questions about its chemical bonding are still being hotly debated. The complex electronic structure of C$_2$ is a consequence of its dense manifold of near-degenerate, low-lying electronic states. A global multi-state diabatic model is proposed here to disentangle the numerous configuration interactions within four symmetry manifolds of C$_2$ ($^{1}\Pi_g$, $^{3}\Pi_g$, $^{1}\Sigma_u^+$, and $^{3}\Sigma_u^+$). The key concept of our model is the existence of two "valence-hole" configurations, $2\sigma_g^22\sigma_u^11\pi_{u}^33\sigma_g^2$ for $^{1,3}\Pi_g$ states and $2\sigma_g^22\sigma_u^11\pi_{u}^43\sigma_g^1$ for $^{1,3}\Sigma_u^+$ states that derive from $3\sigma_g\leftarrow2\sigma_u$ electron promotion. The lowest-energy state from each of the four C$_2$ symmetry species is dominated by this type of valence-hole configuration at its equilibrium internuclear separation. As a result of their large binding energy (nominal bond order of 3) and correlation with the 2s$^2$2p$^2$+2s2p$^3$ separated-atom configurations, the presence of these valence-hole configurations has a profound impact on the $global$ electronic structure and unimolecular dynamics of C$_2$.

Singlet fission is a form of multiple exciton generation which occurs in organic chromophores when a high energy singlet exciton separates into two lower energy triplet excitons, each with approximately half the singlet energy. Since this process is spin-allowed it can proceed on an ultrafast timescale of less than several picoseconds, outcompeting most other loss mechanisms and reaching quantitative yields approaching 200%. Due to this high quantum efficiency, the singlet fission process shows promise as a means of reducing thermalisation losses in photovoltaic cells. This would potentially allow for efficiency improvements beyond the thermodynamic limit in a single junction cell. Efforts to incorporate this process into solar photovoltaic cells have spanned a wide range of device structures over the past decade. In this review we compare and categorise these attempts in order to assess the state of the field and identify the most promising avenues of future research and development.

We present updated cosmological constraints from measurements of the gas mass fractions ($f_{gas}$) of massive, dynamically relaxed galaxy clusters. Our new data set has greater leverage on models of dark energy, thanks to the addition of the Perseus Cluster at low redshifts, two new clusters at redshifts $z>0.97$, and significantly longer observations of four clusters at $0.6

Neutrino oscillations occur within the frame of the Standard Model, assuming that a neutrino is composed of a left handed and a right handed mass less fermion. Neutrino oscillations proceed via the 4-component Higgs field as intermediate state., Comment: 6 pages, 2 figures

Petri nets have found widespread use among many application domains, not least due to their human-friendly graphical syntax for the composition of interacting distributed and asynchronous processes and services, based in partial-order dependencies and concurrent executions. Petri nets also come with abstract semantics, and mathematical methods for compositional synthesis, structural checks and behavioural analysis. These have led to the use of various kinds of nets for real-time, distributed and parallel programming languages, software and services systems, with a view to their interfaces and interaction protocols. These affordances make Petri nets invaluable for distributed software architecture approaches focused on components, their mutual dependencies and environment-facing interactions. Quantum computing -- and in particular quantum software engineering -- is in its infancy and could benefit from the accumulated insights of software architecture research and of net theory, its methods, and its applications. In this paper, we establish a connection between Petri nets and quantum systems, such that net theory and the component architecture of nets may help in the synthesis and analysis of abstract software models and their interface protocols in hybrid classical-and-quantum programming languages and services systems. We leverage some insights from net formalisms for software specification for a versatile recipe to bake quantum into extant Petri net flavours, and prove universality and compositionality of Petri nets for quantum programming., Comment: 24 pages incl. supplementary material in appendix. Accepted for the 15th Symposium and Summer School On Service-Oriented Computing (Submitted 2 April 2021, https://www.summersoc.eu). Final revised and authenticated version to appear in Springer CCIS (https://www.springer.com/series/7899)

Dark photons are hypothetical massive vector particles that could mix with ordinary photons. The simplest theoretical model is fully characterised by only two parameters: the mass of the dark photon m$_{\gamma^{\mathrm{D}}}$ and its mixing parameter with the photon, $\varepsilon$. The sensitivity of the SHiP detector is reviewed for dark photons in the mass range between 0.002 and 10 GeV. Different production mechanisms are simulated, with the dark photons decaying to pairs of visible fermions, including both leptons and quarks. Exclusion contours are presented and compared with those of past experiments. The SHiP detector is expected to have a unique sensitivity for m$_{\gamma^{\mathrm{D}}}$ ranging between 0.8 and 3.3$^{+0.2}_{-0.5}$ GeV, and $\varepsilon^2$ ranging between $10^{-11}$ and $10^{-17}$.

Superspreading complicates the study of SARS-CoV-2 transmission. I propose a model for aggregated case data that accounts for superspreading and improves statistical inference. In a Bayesian framework, the model is estimated on German data featuring over 60,000 cases with date of symptom onset and age group. Several factors were associated with a strong reduction in transmission: public awareness rising, testing and tracing, information on local incidence, and high temperature. Immunity after infection, school and restaurant closures, stay-at-home orders, and mandatory face covering were associated with a smaller reduction in transmission. The data suggests that public distancing rules increased transmission in young adults. Information on local incidence was associated with a reduction in transmission of up to 44% (95%-CI: [40%, 48%]), which suggests a prominent role of behavioral adaptations to local risk of infection. Testing and tracing reduced transmission by 15% (95%-CI: [9%,20%]), where the effect was strongest among the elderly. Extrapolating weather effects, I estimate that transmission increases by 53% (95%-CI: [43%, 64%]) in colder seasons.

The economic value of a photovoltaic installation depends upon both its lifetime and power conversion efficiency. Progress towards the latter includes mechanisms to circumvent the Shockley- Queisser limit, such as tandem designs and multiple exciton generation (MEG). Here we explain how both silicon tandem and MEG enhanced silicon cell architectures result in lower cell operating temperatures, increasing the device lifetime compared to standard c-Si cells. Also demonstrated are further advantages from MEG enhanced silicon cells: (i) the device architecture can completely circumvent the need for current-matching; and (ii) upon degradation, tetracene, a candidate singlet fission (a form of MEG) material, is transparent to the solar spectrum. The combination of (i) and (ii) mean that the primary silicon device will continue to operate with reasonable efficiency even if the singlet fission layer degrades. The lifespan advantages of singlet fission enhanced silicon cells, from a module perspective, are compared favorably alongside the highly regarded perovskite/silicon tandem and conventional c-Si modules., Comment: 16 pages, 4 figures

We propose to build and operate a detector that, for the first time, will measure the process $pp\to\nu X$ at the LHC and search for feebly interacting particles (FIPs) in an unexplored domain. The TI18 tunnel has been identified as a suitable site to perform these measurements due to very low machine-induced background. The detector will be off-axis with respect to the ATLAS interaction point (IP1) and, given the pseudo-rapidity range accessible, the corresponding neutrinos will mostly come from charm decays: the proposed experiment will thus make the first test of the heavy flavour production in a pseudo-rapidity range that is not accessible by the current LHC detectors. In order to efficiently reconstruct neutrino interactions and identify their flavour, the detector will combine in the target region nuclear emulsion technology with scintillating fibre tracking layers and it will adopt a muon identification system based on scintillating bars that will also play the role of a hadronic calorimeter. The time of flight measurement will be achieved thanks to a dedicated timing detector. The detector will be a small-scale prototype of the scattering and neutrino detector (SND) of the SHiP experiment: the operation of this detector will provide an important test of the neutrino reconstruction in a high occupancy environment., Comment: Letter of Intent

In the interstellar medium, carbon is distributed between the gas and solid phases. However, while about half of the expected carbon abundance can be accounted for in the gas phase, there is considerable uncertainty as to the amount incorporated in interstellar dust. The aliphatic component of the carbonaceous dust is of particular interest because it produces a significant 3.4 $\mu$m absorption feature when viewed against a background radiation source. The optical depth of the 3.4 $\mu$m absorption feature is related to the number of aliphatic carbon C-H bonds along the line of sight. It is possible to estimate the column density of carbon locked up in the aliphatic hydrocarbon component of interstellar dust from quantitative analysis of the 3.4 $\mu$m interstellar absorption feature providing that the absorption coefficient of aliphatic hydrocarbons incorporated in the interstellar dust is known. We generated laboratory analogues of interstellar dust by experimentally mimicking interstellar/circumstellar conditions. The resultant spectra of these dust analogues closely match those from astronomical observations. The measurements of the absorption coefficient of aliphatic hydrocarbons incorporated in the analogues were carried out by a procedure which combined FTIR and $^{13}$C NMR spectroscopies. The absorption coefficients obtained for both interstellar analogues were found to be in close agreement (4.76(8) $\times$ 10$^{-18}$ cm group$^{-1}$ and 4.69(14) $\times$ 10$^{-18}$ cm group$^{-1}$), less than half those obtained in studies using small aliphatic molecules. The results thus obtained permit direct calibration of the astronomical observations, providing rigorous estimates of the amount of aliphatic carbon in the interstellar medium.

In the interstellar medium, the cosmic elemental carbon abundance includes the total carbon in both gas and solid phases. The aim of the study was to trial a new method for measuring the amount and distribution of aliphatic carbon within interstellar dust over wide fields of view of our Galaxy. This method is based on measurement of the 3.4 $\mu$m absorption feature from aliphatic carbonaceous matter. This can readily be achieved for single sources using IR spectrometers. However, making such measurements over wide fields requires an imaging IR camera, equipped with narrow-band filters that are able to sample the spectrum. While this cannot produce as good a determination of the spectra, the technique can be applied to potentially tens to hundreds of sources simultaneously, over the field of view of the camera. We examined this method for a field in the centre of the Galaxy, and produced a map showing the variation of 3.4 $\mu$m optical depth across it.

Rational respondents to economic surveys may report as a point forecast any measure of the central tendency of their (possibly latent) predictive distribution, for example the mean, median, mode, or any convex combination thereof. We propose tests of forecast rationality when the measure of central tendency used by the respondent is unknown. We overcome an identification problem that arises when the measures of central tendency are equal or in a local neighborhood of each other, as is the case for (exactly or nearly) symmetric distributions. As a building block, we also present novel tests for the rationality of mode forecasts. We apply our tests to income forecasts from the Federal Reserve Bank of New York's Survey of Consumer Expectations. We find these forecasts are rationalizable as mode forecasts, but not as mean or median forecasts. We also find heterogeneity in the measure of centrality used by respondents when stratifying the sample by past income, age, job stability, and survey experience.

Photochemical upconversion is a promising way to boost the efficiency of solar cells using triplet exciton annihilation. Currently, predicting the performance of photochemical upconversion devices is challenging. We present an open source software package which takes experimental parameters as inputs and gives the figure of merit of an upconversion system, enabling theory-driven design of better solar energy devices. We incorporate the statistical distribution of triplet excitons between the sensitizer and the emitter. Using the dynamic quenching effect of the sensitizer on emitter triplet excitons, we show that the optimal sensitizer concentration can be below the sensitizer solubility limit in liquid devices. These theoretical contributions can explain, without use of heavy atom-induced triplet exciton formation or phenyl group rotation, the experimental failure of zinc octaethylporphyrin to effectively sensitize diphenylanthracene, where platinum octaethylporphyrin succeeds. Our predictions indicate a change in direction for device design that will reduce triplet exciton losses., Comment: 11 pages, 11 figures. For software, see http://laszlofrazer.com

Understanding and controlling exciton transport is a strategic way to enhance the optoelectronic properties of high-performance organic devices. In this article we study triplet exciton migration in crystalline poly($p$-phenylene vinylene) polymer (PPV) using comprehensive electronic structure and quantum dynamical methods. We solve the coupled electron-nuclear dynamics for the triplet energy migrating between two neighboring Frenkel sites in J- and H-aggregate arrangements. From the two-site model we extract key parameters for use with a master-equation approach that allows us to treat nanosize systems where time-dependent Schr\"odinger equation becomes intractable. We calculate the transient exciton density evolution and determine the diffusion constants along the principal crystal axes of the PPV. The triplet diffusion is characterized by two distinctive components: fast intrachain, and slow interchain. At room temperature the interchain diffusion coefficients are found to be $D_a=0.89\cdot10^{-2}$ cm$^2$s$^{-1}$ and $D_b=1.49\cdot10^{-2}$ cm$^2$s$^{-1}$ along the respective $\bar{a}$- and $\bar{b}$-axes, and the intrachain is $D_c=3.03$ cm$^2$s$^{-1}$ along the fast $\bar{c}$-axis. The exceptionally high exciton mobility along the $\pi$-conjugated backbone facilitates rapid triplet migration over long distances. Our results can be utilized in the design of efficient energy conversion and light-emitting devices with desired solid-state properties., Comment: Final version after corrections and improvements

Passive multi-target tracking applications require the integration of multiple spatially distributed sensor measurements to distinguish true tracks from ghost tracks. A popular multi-target tracking approach for these applications is the particle filter implementation of Mahler's probability hypothesis density (PHD) filter, which jointly updates the union of all target state space estimates without requiring computationally complex measurement-to-track data association. Although this technique is attractive for implementation in computationally limited platforms, the performance benefits can be significantly overshadowed by inefficient sampling of the target birth particles over the region of interest. We propose a multi-sensor extension of the adaptive birth intensity PHD filter described in (Ristic, 2012) to achieve efficient birth particle sampling driven by online sensor measurements from multiple sensors. The proposed approach is demonstrated using distributed time-difference-of-arrival (TDOA) and frequency-difference-of-arrival (FDOA) measurements, in which we describe exact techniques for sampling from the target state space conditioned on the observations. Numerical results are presented that demonstrate the increased particle density efficiency of the proposed approach over a uniform birth particle sampler., Comment: 21st International Conference on Information Fusion