We present a multi-agent system for automation of scientific research tasks, cmbagent (this https URL). The system is formed by about 30 Large Language Model (LLM) agents and implements a Planning & Control strategy to orchestrate the agentic workflow, with no human-in-the-loop at any point. Each agent specializes in a different task (performing retrieval on scientific papers and codebases, writing code, interpreting results, critiquing the output of other agents) and the system is able to execute code locally. We successfully apply cmbagent to carry out a PhD level cosmology task (the measurement of cosmological parameters using supernova data) and evaluate its performance on two benchmark sets, finding superior performance over state-of-the-art LLMs. The source code is available on GitHub, demonstration videos are also available, and the system is deployed on HuggingFace and will be available on the cloud.

We investigate how stellar disks sustain their ultrathin structure throughout their evolution. We follow the evolution of ultrathin stellar disks with varying dark matter (DM) halo concentration ($c$) using collisionless $N$-body simulations with \texttt{AREPO}. We test models embedded in steep ($c = 12$), shallow ($c = 2$), and intermediate ($c = 6$) DM concentrations. Our models match the observed structural properties of the stellar disk in the low surface brightness (LSB) ultrathin galaxy FGC~2366, specifically its surface brightness, disk scalelength, and vertical thinness ($h_{z}/R_{D} = 0.1$), while excluding gas, allowing us to isolate the effects of DM. The internal disk heating mechanism driven by bars is suppressed in the LSB ultrathin stellar disks regardless of the DM concentration. The ratio of disk thickness ($h_z$) to scalelength ($R_D$) remains constant at $\leq 0.1$ throughout their evolution. To clearly establish that the LSB nature of stellar disks is the key to preventing disk thickening, we construct the initial conditions by increasing the stellar mass fraction from $f_{s} \sim 0.01$ to $0.02$ and $0.04$, respectively, while keeping the total mass equal to $10^{11} M_\odot$ and $h_z/R_D \leq 0.1$ unchanged. We find that models with a higher stellar mass fraction embedded in a shallow DM potential ($c = 2$) form bars and undergo significant disk thickening ($h_{z}/R_{D} \gg 0.1$) concurrent with the bar growth. We conclude that if the LSB disks are thin to begin with, they remain so throughout their evolution in isolation, regardless of the concentration of the DM halo.

mRNA translation is a crucial process that leads to protein synthesis in living cells. Therefore, it is a process that needs to work optimally for a cell to stay healthy and alive. With advancements in microscopy and novel experimental techniques, a lot of the intricate details about the translation mechanism are now known. However, the why and how of this mechanism are still ill understood, and therefore, is an active area of research. Theoretical studies of mRNA translation typically view it in terms of the Totally Asymmetric Simple Exclusion Process or TASEP. Various works have used the TASEP model in order to study a wide range of phenomena and factors affecting translation, such as ribosome traffic on an mRNA under noisy (codon-dependent or otherwise) conditions, ribosome stalling, premature termination, ribosome reinitiation and dropoff, codon-dependent elongation and competition among mRNA for ribosomes, among others. In this review, we relay the history and physics of the translation process in terms of the TASEP framework. In particular, we discuss the viability and evolution of this model and its limitations while also formulating the reasons behind its success. Finally, we also identify gaps in the existing literature and suggest possible extensions and applications that will lead to a better understanding of ribosome traffic on the mRNA.

Since the ground-breaking discovery of the quantum Hall effect, half-quantized quantum Hall plateaus have been some of the most studied and sought-after states. Their importance stems not only from the fact that they transcend the composite fermion framework used to explain fractional quantum Hall states (such as Laughlin states). Crucially, they hold promise for hosting non-Abelian excitations, which are essential for developing topological qubits - key components for fault-tolerant quantum computing. In this work, we show that these coveted half-quantized plateaus can appear in more than one unexpected way. We report the observation of fractional states with conductance quantization at $\nu_H = 5/2$ arising due to charge equilibration in the confined region of a quantum point contact in monolayer graphene.

Traditional quantum speed limits formulated in density matrix space perform poorly for dynamics beyond unitary, as they are generally unattainable and fail to characterize the fastest possible dynamics. To address this, we derive two distinct quantum speed limits in Liouville space for Completely Positive and Trace-Preserving (CPTP) dynamics that outperform previous bounds. The first bound saturates for time-optimal CPTP dynamics, while the second bound is exact for all states and all CPTP dynamics. Our bounds have a clear physical and geometric interpretation arising from the uncertainty of superoperators and the geometry of quantum evolution in Liouville space. They can be regarded as the generalization of the Mandelstam-Tamm bound, providing uncertainty relations between time, energy, and dissipation for open quantum dynamics. Additionally, our bounds are significantly simpler to estimate and experimentally more feasible as they require to compute or measure the overlap of density matrices and the variance of the Liouvillian. We have also obtained the form of the Liouvillian, which generates the time-optimal (fastest) CPTP dynamics for given initial and final states. We give two important applications of our bounds. First, we show that the speed of evolution in Liouville space bounds the growth of the spectral form factor and Krylov complexity of states, which are crucial for studying information scrambling and quantum chaos. Second, using our bounds, we explain the Mpemba effect in non-equilibrium open quantum dynamics.

Energy prediction in buildings plays a crucial role in effective energy management. Precise predictions are essential for achieving optimal energy consumption and distribution within the grid. This paper introduces a Long Short-Term Memory (LSTM) model designed to forecast building energy consumption using historical energy data, occupancy patterns, and weather conditions. The LSTM model provides accurate short, medium, and long-term energy predictions for residential and commercial buildings compared to existing prediction models. We compare our LSTM model with established prediction methods, including linear regression, decision trees, and random forest. Encouragingly, the proposed LSTM model emerges as the superior performer across all metrics. It demonstrates exceptional prediction accuracy, boasting the highest R2 score of 0.97 and the most favorable mean absolute error (MAE) of 0.007. An additional advantage of our developed model is its capacity to achieve efficient energy consumption forecasts even when trained on a limited dataset. We address concerns about overfitting (variance) and underfitting (bias) through rigorous training and evaluation on real-world data. In summary, our research contributes to energy prediction by offering a robust LSTM model that outperforms alternative methods and operates with remarkable efficiency, generalizability, and reliability.

Jet quenching serves as a key probes of the Quark-Gluon Plasma (QGP) in heavy-ion collisions. This proceedings presents recent results from RHIC and LHC on jet energy loss, acoplanarity, and the flavour and path-length dependence of Parton energy loss, providing critical constraints on QGP properties and theoretical models. Upcoming data taking campaigns at RHIC and the LHC will offer enhanced precision and extended kinematic reach to further advance our understanding of jet-medium interactions.

The STAR Collaboration at the Relativistic Heavy Ion Collider reports the first measurement of inclusive jet production in peripheral and central Au+Au collisions at $\sqrt{s_{NN}}$=200 GeV. Jets are reconstructed with the anti-k$_{T}$ algorithm using charged tracks with pseudorapidity |\eta|<1.0 and transverse momentum $0.2

The Grover search algorithm performs an unstructured search of a marked item in a database quadratically faster than classical algorithms and is shown to be optimal. Here, we show that if the search space is divided into two blocks with the local query operators and the global operators satisfy certain condition, then it is possible to achieve an improvement of bi-quadratic speed-up. Furthermore, we investigate the bi-quadratic speed-up in the presence of noise and show that it can tolerate noisy scenario. This may have potential applications for diverse fields, including database searching, and optimization, where efficient search algorithms play a pivotal role in solving complex computational problems.

We present the analytical calculation of entanglement entropy for a class of two dimensional field theories governed by the symmetries of the Galilean conformal algebra, thus providing a rare example of such an exact computation. These field theories are the putative holographic duals to theories of gravity in three-dimensional asymptotically flat spacetimes. We provide a check of our field theory answers by an analysis of geodesics. We also exploit the Chern-Simons formulation of three-dimensional gravity and adapt recent proposals of calculating entanglement entropy by Wilson lines in this context to find an independent confirmation of our results from holography.

Muons are the most abundant charged particles arriving at sea level originating from the decay of secondary charged pions and kaons. These secondary particles are created when high-energy cosmic rays hit the atmosphere interacting with air nuclei initiating cascades of secondary particles which led to the formation of extensive air showers (EAS). They carry essential information about the extra-terrestrial events and are characterized by large flux and varying angular distribution. To account for open questions and the origin of cosmic rays, one needs to study various components of cosmic rays with energy and arriving direction. Because of the close relation between muon and neutrino production, it is the most important particle to keep track of. We propose a novel tracking algorithm based on the Geometric Deep Learning approach using graphical structure to incorporate domain knowledge to track cosmic ray muons in our 3-D scintillator detector. The detector is modeled using the GEANT4 simulation package and EAS is simulated using CORSIKA (COsmic Ray SImulations for KAscade) with a focus on muons originating from EAS. We shed some light on the performance, robustness towards noise and double hits, limitations, and application of the proposed algorithm in tracking applications with the possibility to generalize to other detectors for astrophysical and collider experiments.

Gamma-ray bursts (GRBs) are intense, short-lived bursts of gamma-ray radiation observed up to a high redshift ($z \sim 10$) due to their luminosities. Thus, they can serve as cosmological tools to probe the early Universe. However, we need a large sample of high$-z$ GRBs, currently limited due to the difficulty in securing time at the large aperture Telescopes. Thus, it is painstaking to determine quickly whether a GRB is high$z$ or low$-z$, which hampers the possibility of performing rapid follow-up observations. Previous efforts to distinguish between high$-$ and low$-z$ GRBs using GRB properties and machine learning (ML) have resulted in limited sensitivity. In this study, we aim to improve this classification by employing an ensemble ML method on 251 GRBs with measured redshifts and plateaus observed by the Neil Gehrels Swift Observatory. Incorporating the plateau phase with the prompt emission, we have employed an ensemble of classification methods to enhance the sensitivity unprecedentedly. Additionally, we investigate the effectiveness of various classification methods using different redshift thresholds, $z_{threshold}$=$z_t$ at $z_{t}=$ 2.0, 2.5, 3.0, and 3.5. We achieve a sensitivity of 87\% and 89\% with a balanced sampling for both $z_{t}=3.0$ and $z_{t}=3.5$, respectively, representing a 9\% and 11\% increase in the sensitivity over Random Forest used alone. Overall, the best results are at $z_{t} = 3.5$, where the difference between the sensitivity of the training set and the test set is the smallest. This enhancement of the proposed method paves the way for new and intriguing follow-up observations of high$-z$ GRBs.

Dimerization and subsequent aggregation of polymers and biopolymers often occur under nonequilibrium conditions. When the initial state of the polymer is not collapsed or the final folded native state, the dynamics of dimerization can follow a course sensitive to both the initial conditions and the conformational dynamics. Here we study the dimerization process by using computer simulations and analytical theory where both the two monomeric polymer chains are in the elongated state and are initially placed at a separation distance, d0. Subsequent dynamics lead to the concurrent processes of collapse, dimerization and/or escape. We employ Langevin dynamics simulations with a coarse-grained model of the polymer to capture certain aspects of the dimerization process. At separations d0 much shorter than the length of the monomeric polymer, the dimerization could happen fast and irreversibly, from the partly extended polymer state itself. At an initial separation larger than a critical distance, dc, the polymer collapse precedes dimerization and a significant number of single polymers do not dimerize within the time scale of simulations. To quantify these competition, we introduce several time-dependent order parameters, namely, (i) the time-dependent radius of gyration of individual polymers describing the conformational state of the polymer, (ii) a centre-to-centre of mass distance parameter RMM, and (iii) a time dependent overlap function Q(t) between the two monomeric polymers, mimicking contact order parameter popular in protein folding. In order to better quantify the findings, we perform a theoretical analysis to capture the stochastic processes of collapse and dimerization by using dynamical disorder model.

Transition-metal dichalcogenides (TMDs) host tightly bound quasi-particles called excitons. Based on spin and momentum selection rules, these excitons can be either optically bright or dark. In tungsten-based TMDs, momentum-forbidden dark exciton is the energy ground state and therefore it strongly affect the emission properties. In this work, we brighten the momentum forbidden dark exciton by placing WS$_2$ on top of nanotextured substrates which put the WS$_2$ layer under tensile strain, modifying electronic bandstructure. This enables phonon assisted scattering of exciton between momentum valleys, thereby brightening momentum forbidden dark excitons. Our results will pave the way to design ultrasensitive strain sensing devices based on TMDs.

Conventional continuous quantum heat engines with incoherent heat transfer perform poorly as they exploit two-body interactions between the system and hot or cold baths, thus having limited capability to outperform their classical counterparts. We introduce distinct continuous quantum heat engines that utilize coherent heat transfer with baths, yielding genuine quantum enhancement in performance. These coherent engines consist of one qutrit system and two photonic baths and enable coherent heat transfer via two-photon transitions involving three-body interactions between the system and hot and cold baths. We demonstrate that coherent engines deliver significantly higher power output with much greater reliability, i.e., lower signal-to-noise ratio of the power, by hundreds of folds over their incoherent counterparts. Importantly, coherent engines can operate close to or at the maximal achievable reliability allowed by the quantum thermodynamic uncertainty relation. Moreover, coherent engines manifest more nonclassical features than incoherent engines because they violate the classical thermodynamic uncertainty relation by a greater amount and for a wider range of parameters. These genuine enhancements in the performance of coherent engines are directly attributed to their capacity to harness higher energetic coherence for the resonant driving case. The experimental feasibility of coherent engines and the improved understanding of how quantum properties can enhance performance may find applications in quantum-enabled technologies.

Transition metal dichalcogenide (TMD) nanoscrolls (NS) exhibit significant photoluminescence (PL) signals despite their multilayer structure, which cannot be explained by the strained multilayer description of NS. Here, we investigate the interlayer interactions in NS to address this discrepancy. The reduction of interlayer interactions in NS is attributed to two factors: (1) the symmetry-broken mixed stacking order between neighbouring layers due to misalignment, and (2) the high inhomogeneity in the strain landscape resulting from the unique Archimedean spiral-like geometry with positive eccentricity. These were confirmed through transmission electron microscopy, field emission scanning electron microscopy and atomic force microscopy. To probe the effect of reduction of interlayer interactions in multilayered MoS$_2$ nanoscrolls, low-temperature PL spectroscopy was employed investigating the behaviour of K-point excitons. The effects of reduced interlayer interactions on exciton-phonon coupling (EXPC), exciton energy, and exciton oscillator strength are discussed, providing insights into the unique properties of TMD nanoscrolls.

Non-Abelian anyons, a promising platform for fault-tolerant topological quantum computation, adhere to the charge super-selection rule (cSSR), which imposes restrictions on physically allowed states and operations. However, the ramifications of cSSR and fusion rules in anyonic quantum information theory remain largely unexplored. In this study, we unveil that the information-theoretic characteristics of anyons diverge fundamentally from those of non-anyonic systems such as qudits, bosons, and fermions and display intricate structures. In bipartite anyonic systems, pure states may have different marginal spectra, and mixed states may contain pure marginal states. More striking is that in a pure entangled state, parties may lack equal access to entanglement. This entanglement asymmetry is manifested in quantum teleportation employing an entangled anyonic state shared between Alice and Bob, where Alice can perfectly teleport unknown quantum information to Bob, but Bob lacks this capability. These traits challenge conventional understanding, necessitating new approaches to characterize quantum information and correlations in anyons. We expect that these distinctive features will also be present in non-Abelian lattice gauge field theories. Our findings significantly advance the understanding of the information-theoretic aspects of anyons and may lead to realizations of quantum communication and cryptographic protocols where one party holds sway over the other.

We present analyses of Suzaku XIS light curves and spectra of the BL Lac object OJ 287 with observations positioned primarily around proposed recurrent optical outbursts. The first two observations were performed in 2007 April 10 - 13 (epoch 1) and 2007 November 7 - 9 (epoch 2) that respectively correspond to a low and a high optical state and which, within the binary supermassive black hole model for OJ 287, precede and follow the impact flare. The last three observations, made consecutively during 2015 May 3 - 9 (epoch 3), were during the post-impact state of the 2013 disc impact and are the longest continuous X-ray observation of OJ 287 taken before the optical outburst in 2015 December. Intraday variability is found in both the soft (0.5 - 2 keV) and hard (2 - 10 keV) bands. The discrete correction function analysis of the light curves in both bands peaks at zero lag during epochs 2 and 3, indicating that the emission in both bands was cospatial and emitted from the same population of leptons. Power spectral densities of all three light curves are red noise dominated, with a rather wide range of power spectrum slopes. These X-ray spectra are overall consistent with power-laws but with significantly different spectral indices. In the 2015 observations the X-ray spectrum softens during the flare, showing an obvious soft X-ray excess that was not evident in the 2007 observations. We discuss the implications of these observations on the jet, the possible accretion disc, and the binary supermassive black hole model proposed for the nearly periodic optical flaring of OJ 287.

The study of information revivals, witnessing the violation of certain data-processing inequalities, has provided an important paradigm in the study of non-Markovian quantum stochastic processes. Although often used interchangeably, we argue here that the notions of ``revivals'' and ``backflows'', i.e., flows of information from the environment back into the system, are distinct: an information revival can occur without any backflow ever taking place. In this paper, we examine in detail the phenomenon of non-causal revivals and relate them to the theory of short Markov chains and squashed non-Markovianity. We also provide an operational condition, in terms of system-only degrees of freedom, to witness the presence of genuine backflow that cannot be explained by non-causal revivals. As a byproduct, we demonstrate that focusing on processes with genuine backflows, while excluding those with only non-causal revivals, resolves the issue of non-convexity of Markovianity, thus enabling the construction of a convex resource theory of genuine quantum non-Markovianity.

The prompt phase X- and $\gamma$-ray light curves of gamma-ray bursts (GRBs) exhibit erratic and complex behaviour, often with multiple pulses. The temporal shape of individual pulses is often modelled as 'fast rise exponential decay' (FRED). Here, we introduce a novel fitting function to quantify pulse asymmetry. We conduct a light curve and a time-resolved spectral analysis on 61 pulses from 22 GRBs detected by the Fermi Gamma-ray Burst Monitor. Contrary to previous claims, we find that only $\sim 50\%$ of pulse lightcurves in our sample show a FRED shape, while about $25\%$ have a symmetric lightcurve, and the other $25\%$ have a mixed shape. Furthermore, our analysis reveals a clear trend: in multi-pulse bursts, the initial pulse tends to exhibit the most symmetric light curve, while subsequent pulses become increasingly asymmetric, adopting a more FRED-like shape. Additionally, we correlate the temporal and spectral shapes of the pulses. By fitting the spectra with the classical "Band" function, we find a moderate positive Spearman correlation index of 0.23 between pulse asymmetry and the low-energy spectral index $\alpha_{\max}$ (the maximum value across all time bins covering an individual pulse). Thus, during GRB light curves, the pulses tend to get more asymmetric and spectrally softer with time. We interpret this as a transition in the dominant emission mechanism from photospheric (symmetric-like and hard) to non-thermal emission above the photosphere and show that this interpretation aligns with a GRB jet Lorentz factor of the order of a few 10s in many cases.