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Tuning the density of resident electrons or holes in semiconductors provides crucial insight into the composition of excitonic complexes that are observed as absorption or photoluminescence resonances in optical studies. Moreover, we can change the way these resonances shift and broaden in energy by controlling the quantum numbers of the resident carriers with magnetic fields and doping levels, and by selecting the quantum numbers of the photoexcited or recombining electron-hole (e-h) pair through optical polarization. We discuss the roles of distinguishability and optimality of excitonic complexes, showing them to be key ingredients that determine the energy shifts and broadening of optical resonances in charge-tunable semiconductors. A distinguishable e-h pair means that the electron and hole undergoing photoexcitation or recombination have quantum numbers that are not shared by any of the resident carriers. An optimal excitonic complex refers to a complex whose particles come with all available quantum numbers of the resident carriers. All optical resonances may be classified as either distinct or indistinct depending on the distinguishability of the e-h pair, and the underlying excitonic complex can be classified as either optimal or suboptimal. The universality of these classifications, inherited from the fundamental Pauli exclusion principle, allows us to understand how optical resonances shift in energy and whether they should broaden as doping is increased. This understanding is supported by conclusive evidence that the decay of optical resonances cannot be simply attributed to enhanced screening when resident carriers are added to a semiconductor. Finally, applying the classification scheme in either monolayer or moire heterobilayer systems, we relate the energy shift and amplitude of the neutral exciton resonance to the compressibility of the resident carrier gas., Comment: 22 pages, 16 figures, we welcome your feedback

Treating the trion problem as an effective two-body system with exciton and electron components, we identify component exchange as the reason leading to trion formation. This mechanism can be visualized as a hole that toggles back and forth between two electrons. The coined term component exchange is meant to inform that the repeated change of the electron component of the exciton originates from the exchange interaction. We develop a Bethe-Salpeter Equation for trions, showing that a bound trion state emerges if the electron and electron of the exciton are distinguishable particles (e.g., having opposite spins or residing in different valleys of the Brillouin zone). Similar to numerical techniques that treat the trion as a three-body problem, the trion Bethe-Salpeter Equation yields similar binding energy without using parameters beyond effective masses and dielectric constants., Comment: 12 pages, 7 figures. We welcome your feedback. If we missed a citation to a RELEVANT paper, please mention a specific place in the text that we should add the citation

The $\nu_M{\rm SM}$ is defined as the SM extended to include dimension-5 operators. In this model neutrino masses violate lepton number, and two parameters of the lepton mixing matrix, the Majorana phases, are yet to be constrained. One combination of these phases and the neutrino masses, often denoted by $m_{ee}$, is probed by neutrinoless double beta decays ($0\nu\beta\beta$). We explore what information may be obtained beyond $0\nu\beta\beta$, and how it depends on the lightest neutrino mass. We point out that with current central values of the mixing parameters, $\Delta L_e=2$ and $\Delta L_e=\Delta L_\mu = 1$ (or $\Delta L_e=2$ and $\Delta L_\mu = 2$) processes cannot simultaneously vanish, providing a no-lose theorem, in principle, for excluding the $\nu_M{\rm SM}$, even in the case of normal mass ordering.

The optical emission spectra of semiconducting transition-metal dichalcogenide monolayers highlight fascinating recombination processes of charged excitons (trions). When charge tunable WSe2 monolayers are moderately doped with electrons, a strong luminescence peak emerges just below the well-understood spectral lines associated with the recombination of negatively charged bright and dark trions. Despite previous investigations, its origin remains elusive. Here, we demonstrate that this luminescence peak is the result of electron-electron assisted recombination that brightens the dark trion emission. Supporting evidence for this second-order recombination process comes from identifying the equivalent brightened emission of positively charged dark trions when the monolayer is electrostatically doped with holes. Remarkably, the discovered hole-hole assisted luminescence peak emerges in the near infrared, about 500 meV below the well-studied spectral region of excitons and trions. In addition to identifying new recombination channels of these excitonic complexes, our findings accurately determine the spin-split energies of the conduction and valence bands. Both of which play crucial roles in understanding the optical properties of WSe2 based homo- and hetero-structures., Comment: 13 pages, 4 figures

We present a new method to solve the dynamical Bethe-Salpeter Equation numerically. The method allows one to investigate the effects of dynamical dielectric screening on the spectral position of excitons in transition-metal dichalcogenide monolayers. The dynamics accounts for the response of optical phonons in the materials below and on top the monolayer to the electric field lines between the electron and hole of the exciton. The inclusion of this effect unravels the origin of a counterintuitive energy blueshift of the exciton resonance, observed recently in monolayer semiconductors that are supported on ionic crystals with large dielectric constants. A surprising result is that while energy renormalization of a free electron in the conduction band or a free hole in the valence band is controlled by the low-frequency dielectric constant, the bandgap energy introduces a phase between the photoexcited electron and hole, rendering contributions from the high-frequency dielectric constant also important when evaluating self-energies of the exciton components. As a result, bandgap renormalization of the exciton is not the sum of independent contributions from energy shifts of the conduction and valence bands. The theory correctly predicts the energy shifts of exciton resonances in various dielectric environments that embed two-dimensional semiconductors., Comment: 13 pages, 7 figures. We welcome your feedback

Coulomb interactions in atomically thin materials are uniquely sensitive to variations in the dielectric screening of the environment, which can be used to control quasiparticles and exotic quantum many-body phases. A static approximation of the dielectric response, where increased dielectric screening is predicted to cause an energy redshift of the exciton resonance, has been until now sufficient. Here, we use charge-tunable exciton resonances to study screening effects in transition metal dichalcogenide monolayers embedded in materials with dielectric constants ranging from 4 to more than 1000. In contrast to expectations, we observe a blueshift of the exciton resonance exceeding 30 meV for larger dielectric constant environments. By employing a dynamical screening model, we find that while the exciton binding energy remains mostly controlled by the static dielectric response, the exciton self-energy is dominated by the high-frequency response. Dielectrics with markedly different static and high-frequency screening enable the selective addressing of distinct many-body effects in layered materials and their heterostructures, expanding the tunability range and offering new routes to detect and control correlated quantum many-body states and to design optoelectronic and quantum devices., Comment: 10 pages, 4 figures. SI: 11 pages, 6 figures. We welcome your feedback!

Given the generational gap in available hardware between lay practitioners and the most endowed institutions, LLMs are becoming increasingly inaccessible as they grow in size. Whilst many approaches have been proposed to compress LLMs to make their resource consumption manageable, these methods themselves tend to be resource intensive, putting them out of the reach of the very user groups they target. In this work, we explore the problem of structured pruning of LLMs using only forward passes. We seek to empower practitioners to prune models so large that their available hardware has just enough memory to run inference. We develop Bonsai, a gradient-free, perturbative pruning method capable of delivering small, fast, and accurate pruned models. We observe that Bonsai outputs pruned models that (i) outperform those generated by more expensive gradient-based structured pruning methods, and (ii) are twice as fast (with comparable accuracy) as those generated by semi-structured pruning methods requiring comparable resources as Bonsai. We also leverage Bonsai to produce a new sub-2B model using a single A6000 that yields state-of-the-art performance on 4/6 tasks on the Huggingface Open LLM leaderboard., Comment: 15 pages, 4 fiigures, 15 tables

The X-ray absorption (XA) spectra of aqueous ammonia and ammonium are computed using a combination of coupled cluster singles and doubles (CCSD) with different quantum mechanical and molecular mechanical embedding schemes. Specifically, we compare frozen Hartree--Fock (HF) density embedding, polarizable embedding (PE), and polarizable density embedding (PDE). Integrating CCSD with frozen HF density embedding is possible within the CC-in-HF framework, which circumvents the conventional system-size limitations of standard coupled cluster methods. We reveal similarities between PDE and frozen HF density descriptions, while PE spectra differ significantly. By including approximate triple excitations, we also investigate the effect of improving the electronic structure theory. The spectra computed using this approach show an improved intensity ratio compared to CCSD-in-HF. Charge transfer analysis of the excitations shows the local character of the pre-edge and main-edge, while the post-edge is formed by excitations delocalized over the first solvation shell and beyond., Comment: 35 pages, 12 figures

When doped with a high density of mobile charge carriers, monolayer transition-metal dichalcogenide (TMD) semiconductors can host new types of composite many-particle exciton states that do not exist in conventional semiconductors. Such multi-particle bound states arise when a photoexcited electron-hole pair couples to not just a single Fermi sea that is quantum-mechanically distinguishable (as for the case of conventional charged excitons or trions), but rather couples simultaneously to \textit{multiple} Fermi seas, each having distinct spin and valley quantum numbers. Composite six-particle ``hexciton'' states were recently identified in electron-doped WSe$_2$ monolayers, but under suitable conditions they should also form in all other members of the monolayer TMD family. Here we present spectroscopic evidence demonstrating the emergence of many-body hexcitons in charge-tunable WS$_2$ monolayers (at the A-exciton) and MoSe$_2$ monolayers (at the B-exciton). The roles of distinguishability and carrier screening on the stability of hexcitons are discussed., Comment: 7 pages, 3 figs

In order to create machine learning systems that serve a variety of users well, it is vital to not only achieve high average performance but also ensure equitable outcomes across diverse groups. However, most machine learning methods are designed to improve a model's average performance on a chosen end task without consideration for their impact on worst group error. Multitask learning (MTL) is one such widely used technique. In this paper, we seek not only to understand the impact of MTL on worst-group accuracy but also to explore its potential as a tool to address the challenge of group-wise fairness. We primarily consider the standard setting of fine-tuning a pre-trained model, where, following recent work \citep{gururangan2020don, dery2023aang}, we multitask the end task with the pre-training objective constructed from the end task data itself. In settings with few or no group annotations, we find that multitasking often, but not consistently, achieves better worst-group accuracy than Just-Train-Twice (JTT; \citet{pmlr-v139-liu21f}) -- a representative distributionally robust optimization (DRO) method. Leveraging insights from synthetic data experiments, we propose to modify standard MTL by regularizing the joint multitask representation space. We run a large number of fine-tuning experiments across computer vision and natural language processing datasets and find that our regularized MTL approach \emph{consistently} outperforms JTT on both average and worst-group outcomes. Our official code can be found here: \href{https://github.com/atharvajk98/MTL-group-robustness.git}{\url{https://github.com/atharvajk98/MTL-group-robustness}}., Comment: 20 pages, 7 tables, 6 Figures

Large, pre-trained models are problematic to use in resource constrained applications. Fortunately, task-aware structured pruning methods offer a solution. These approaches reduce model size by dropping structural units like layers and attention heads in a manner that takes into account the end-task. However, these pruning algorithms require more task-specific data than is typically available. We propose a framework which combines structured pruning with transfer learning to reduce the need for task-specific data. Our empirical results answer questions such as: How should the two tasks be coupled? What parameters should be transferred? And, when during training should transfer learning be introduced? Leveraging these insights, we demonstrate that our framework results in pruned models with improved generalization over strong baselines., Comment: 8 pages, 7 figures and 3 tables

We consider the task of optimally fine-tuning pre-trained multilingual models, given small amounts of unlabelled target data and an annotation budget. In this paper, we introduce DEMUX, a framework that prescribes the exact data-points to label from vast amounts of unlabelled multilingual data, having unknown degrees of overlap with the target set. Unlike most prior works, our end-to-end framework is language-agnostic, accounts for model representations, and supports multilingual target configurations. Our active learning strategies rely upon distance and uncertainty measures to select task-specific neighbors that are most informative to label, given a model. DeMuX outperforms strong baselines in 84% of the test cases, in the zero-shot setting of disjoint source and target language sets (including multilingual target pools), across three models and four tasks. Notably, in low-budget settings (5-100 examples), we observe gains of up to 8-11 F1 points for token-level tasks, and 2-5 F1 for complex tasks. Our code is released here: https://github.com/simran-khanuja/demux.

Kaon physics is at a turning point -- while the rare-kaon experiments NA62 and KOTO are in full swing, the end of their lifetime is approaching and the future experimental landscape needs to be defined. With HIKE, KOTO-II and LHCb-Phase-II on the table and under scrutiny, it is a very good moment in time to take stock and contemplate about the opportunities these experiments and theoretical developments provide for particle physics in the coming decade and beyond. This paper provides a compact summary of talks and discussions from the Kaons@CERN 2023 workshop., Comment: 55 pages, Summary of Kaons@CERN 23 workshop, references updated, typos fixed, version as published in EPJC

Students' decisions on whether to take a class are strongly affected by whether their friends plan to take the class with them. A student may prefer to be assigned to a course they likes less, just to be with their friends, rather than taking a more preferred class alone. It has been shown that taking classes with friends positively affects academic performance. Thus, academic institutes should prioritize friendship relations when assigning course seats. The introduction of friendship relations results in several non-trivial changes to current course allocation methods. This paper explores how course allocation mechanisms can account for friendships between students and provide a unique, distributed solution. In particular, we model the problem as an asymmetric distributed constraint optimization problem and develop a new dedicated algorithm. Our extensive evaluation includes both simulated data and data derived from a user study on 177 students' preferences over courses and friends. The results show that our algorithm obtains high utility for the students while keeping the solution fair and observing courses' seat capacity limitations.

We present the first successful application of the coupled cluster approach to simulate the X-ray absorption (XA) spectrum of liquid water. The system size limitations of standard coupled cluster theory are overcome by employing a newly developed coupled cluster method for large molecular systems. This method combines coupled cluster singles, doubles, and perturbative triples in a multilevel framework (MLCC3-in-HF) and is able to describe the delicate nature of intermolecular interactions in liquid water. Using molecular geometries from state-of-the-art path-integral molecular dynamics, we obtain excellent agreement with experimental spectra. Additionally, we show that an accurate description of the electronic structure within the first solvation shell is sufficient to model the XA spectrum of liquid water. Furthermore, we present a rigorous charge transfer analysis with unprecedented reliability, achieved through MLCC3-in-HF. This analysis aligns with previous studies regarding the character of the prominent features of the spectrum., Comment: 32 pages, 4+12 figures

The chemical potential u of an electron system is a fundamental property of a solid. A precise measurement of u plays a crucial role in understanding the electron interaction and quantum states of matter. However, thermodynamics measurements in micro and nanoscale samples are challenging because of the small sample volume and large background signals. Here, we report an optical readout technique for u of an arbitrary two-dimensional (2D) material. A monolayer semiconductor sensor is capacitively coupled to the sample. The sensor optical response determines a bias that fixes its chemical potential to the band edge and directly reads u of the sample. We demonstrate the technique in AB-stacked MoTe2/WSe2 moire bilayers. We obtain u with DC sensitivity about 20 ueV/sqrt(Hz), and the compressibility and interlayer electric polarization using AC readout. The results reveal a correlated insulating state at the doping density of one hole per moire unit cell, which evolves from a Mott to a charge-transfer insulator with increasing out-of-plane electric field. Furthermore, we image u and quantify the spatial inhomogeneity of the sample. Our work opens the door for high spatial and temporal resolution measurements of the thermodynamic properties of 2D quantum materials.

We revisit low-temperature optical spectra of transition-metal dichalcogenide monolayers and point to a possible crystallization of electrons (or holes) at low to moderate charge densities. To calculate the excitonic spectra under such conditions, we introduce the recursion method and compute how the charge density affects the energies, linewidths, and oscillator strengths of exciton and trion complexes. Equally important, we study how excitons and trions in the monolayer evolve when the charge particles gradually transition to a periodic Wigner lattice. The results provide valuable information on the ability to detect whether the particles are ordered through the exciton spectrum. Finally, we calculate the change in exciton energy in cases that the added charge particles have similar and dissimilar quantum numbers (spin and valley) to those of the electron or hole in the exciton. The results of this work shed new light on important optical properties of monolayer semiconductors., Comment: 17 pages, 10 figures. We welcome your feedback

Fine-tuning large-scale pretrained models has led to tremendous progress in well-studied modalities such as vision and NLP. However, similar gains have not been observed in many other modalities due to a lack of relevant pretrained models. In this work, we propose ORCA, a general cross-modal fine-tuning framework that extends the applicability of a single large-scale pretrained model to diverse modalities. ORCA adapts to a target task via an align-then-refine workflow: given the target input, ORCA first learns an embedding network that aligns the embedded feature distribution with the pretraining modality. The pretrained model is then fine-tuned on the embedded data to exploit the knowledge shared across modalities. Through extensive experiments, we show that ORCA obtains state-of-the-art results on 3 benchmarks containing over 60 datasets from 12 modalities, outperforming a wide range of hand-designed, AutoML, general-purpose, and task-specific methods. We highlight the importance of data alignment via a series of ablation studies and demonstrate ORCA's utility in data-limited regimes.

The energy band structure of excitons is studied in periodic potentials produced by the short-range interaction between the exciton and electrons of Wigner or Moir\'{e} lattices. Treating the exciton as a point-like dipole that interacts with the periodic potential, we can solve a simple one-body problem that provides valuable information on excitons in many-body problem settings. By employing group theory, we identify the excitonic energy bands that can couple to light and then quantify their energy shifts in response to a change in the period of the potential. This approach allows us to emulate the response of optically active exciton and trion states to a change in electron density. We gain important insights on the relation between the electron order in a Wigner crystal and the energy blueshift of the bright exciton. We discuss the consequences of this relation in the context of optical absorption experiments in monolayer semiconductors., Comment: We welcome and appreciate your feedback

We present a novel approach to spin-adapted coupled cluster theory. This approach is based on the entanglement of an open-shell molecule with electrons in a non-interacting bath; together they form a closed-shell state. For the total system, electron correlation can be added with the standard spin-adapted closed-shell coupled cluster formalism. A projection operator, which enforces conditions on the electrons in the bath, is used to obtain the desired state of the molecular system. This entanglement coupled cluster theory is detailed and proof-of-concept calculations for doublet states are reported. The approach is extendable to open-shell systems with other values of the total spin., Comment: 17 pages, 3 figures and 7 tables

Iterative peer grading activities may keep students engaged during in-class project presentations. Effective methods for collecting and aggregating peer assessment data are essential. Students tend to grade projects favorably. So, while asking students for numeric grades is a common approach, it often leads to inflated grades across all projects, resulting in numerous ties for the top grades. Additionally, students may strategically assign lower grades to others' projects so that their projects will shine. Alternatively, requesting students to rank all projects from best to worst presents challenges due to limitations in human cognitive capacity. To address these issues, we propose a novel peer grading model consisting of (a) an algorithm designed to elicit student evaluations and (b) a median-based voting protocol for aggregating grades to a single ranked order that reduces ties. An application based on our model was deployed and tested in a university course, demonstrating fewer ties between alternatives and a significant decrease in students' cognitive and communication burdens.