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Bipartite entanglement entropy is one of the most useful characterizations of universal properties in a many-body quantum system. Far from equilibrium, there exist two highly effective theories describing its dynamics -- the quasiparticle and membrane pictures. In this work we investigate entanglement dynamics, and these two complementary approaches, in a quantum circuit model perturbed by an impurity. In particular, we consider a dual unitary quantum circuit containing a spatially fixed, non-dual-unitary impurity gate, allowing for differing local Hilbert space dimensions to either side. We compute the entanglement entropy for both a semi-infinite and a finite subsystem within a finite distance of the impurity, comparing exact results to predictions of the effective theories. We find that for a semi-infinite subsystem, both theories agree with each other and the exact calculation. For a finite subsystem, however, both theories qualitatively differ, with the quasiparticle picture predicting a non-monotonic growth in contrast to the membrane picture. We show that such non-monotonic behavior can arise even in random chaotic circuits, pointing to a hitherto unknown shortcoming of the membrane picture in describing such systems., Comment: 5+7 pages, 2+1 figures. v2: Added a section to the Supplemental Material, updated acknowledgments; 5+9 pages, 2+3 figures

High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 535 authors from 84 institutions, 12 pages, 8 figures. v2 is version accepted for publication in Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

Thermal equilibrium states of local quantum many-body systems are notorious for their spatially decaying correlations, which place severe restrictions on the types of many-body entanglement structures that may be observed at finite temperatures. These restrictions may however be defied when an out-of-equilibrium steady state is considered instead. In this paper, we study the entanglement properties of free fermions on a one-dimensional lattice that contains a generic charge- and energy-conserving noninteracting impurity, and that is connected at its edges to two reservoirs with different equilibrium energy distributions. These distributions may differ in either temperature, chemical potential, or both, thereby inducing an external bias. We analytically derive exact asymptotic expressions for several quantum information measures -- the mutual information, its R\'enyi generalizations, and the fermionic negativity -- that quantify the correlation and entanglement between two subsystems located on opposite sides of the impurity. We show that all these measures scale (to a leading order) linearly with the overlap between one subsystem and the mirror image of the other (upon reflection of the latter about the impurity), independently of the distance between the subsystems. While a simple proportionality relation between the negativity and R\'enyi versions of the mutual information is observed to hold at zero temperature, it breaks down at finite temperatures, suggesting that these quantities represent strong long-range correlations of different origins. Our results generalize previous findings that were limited to the case of a chemical-potential bias at zero temperature, rigorously demonstrating that the effect of long-range volume-law entanglement is robust at finite temperatures., Comment: 16+4 pages, 4 figures. v2: Published version, 17+4 pages, 5 figures

The Fourier harmonics, $v_2$ and $v_3$ of negative pions are measured at center-of-mass energy per nucleon pair of $\sqrt{s_{\mathrm{NN}}}$= 17.3 GeV around midrapidity by the CERES/NA45 experiment at the CERN SPS in 0--30\% central PbAu collisions with a mean centrality of 5.5\%. The analysis is performed in two centrality bins as a function of the transverse momentum $\mathrm{p_{\mathrm{T}}}$ from 0.05 GeV/$c$ to more than 2 GeV/$c$. This is the first measurement of the $v^{1/3}_{3}/v^{1/2}_{2}$ ratio as a function of transverse momentum at SPS energies, that reveals, independently of the hydrodynamic models, hydrodynamic behavior of the formed system. For $\mathrm{p_{\mathrm{T}}}$ above 0.5 GeV/$c$, the ratio is nearly flat in accordance with the hydrodynamic prediction and as previously observed by the ATLAS and ALICE experiments at the much higher LHC energies. The results are also compared with the SMASH-vHLLE hybrid model predictions, as well as with the SMASH model applied alone., Comment: 8 pages, 5 figures

It is often stated that if one is presented with a snapshot of the positions of the molecules of a glass and one of a liquid, one is unable to tell the difference. Here we argue instead that given several such snapshots taken over a time-interval, even without specifying the times, there is a definite procedure to assess precisely the level of glassiness: it suffices to concatenate the snapshots side-by-side, and to subject the joint picture to a lossless compression protocol. We argue that the size of the compressed file yields a direct and unambiguous measure of the `vibrational' and `configurational' entropies, and may be used to study the associated glass length scale in or out of equilibrium through the size and frequency of the repeated motifs essential to the compression, a quantity that would diverge at a putative glass transition.

Out-of-equilibrium states of many-body systems tend to evade a description by standard statistical mechanics, and their uniqueness is epitomized by the possibility of certain long-range correlations that cannot occur in equilibrium. In quantum many-body systems, coherent correlations of this sort may lead to the emergence of remarkable entanglement structures. In this work, we analytically study the asymptotic scaling of quantum correlation measures -- the mutual information and the fermionic negativity -- within the zero-temperature steady state of voltage-biased free fermions on a one-dimensional lattice containing a noninteracting impurity. Previously, we have shown that two subsystems on opposite sides of the impurity exhibit volume-law entanglement, which is independent of the absolute distances of the subsystems from the impurity. Here we go beyond that result and derive the exact form of the subleading logarithmic corrections to the extensive terms of correlation measures, in excellent agreement with numerical calculations. In particular, the logarithmic term of the mutual information asymptotics can be encapsulated in a concise formula, depending only on simple four-point ratios of subsystem length-scales and on the impurity scattering probabilities at the Fermi energies. This echoes the case of equilibrium states, where such logarithmic terms may convey universal information about the physical system. To compute these exact results, we devise a hybrid method that relies on Toeplitz determinant asymptotics for correlation matrices in both real space and momentum space, successfully circumventing the inhomogeneity of the system. This method can potentially find wider use for analytical calculations of entanglement measures in similar scenarios., Comment: v1: 21+5 pages, 4 figures; the main results appearing here were originally reported as part of arXiv:2205.12991, and are removed from there to allow a more elaborate discussion. v2: Published version, 21+6 pages, 4+1 figures

Amyotrophic lateral sclerosis is a fatal disease that not only affects movement, speech, and breath but also cognition. Recent studies have focused on the use of language analysis techniques to detect ALS and infer scales for monitoring functional progression. In this paper, we focused on another important aspect, cognitive impairment, which affects 35-50% of the ALS population. In an effort to reach the ALS population, which frequently exhibits mobility limitations, we implemented the digital version of the Edinburgh Cognitive and Behavioral ALS Screen (ECAS) test for the first time. This test which is designed to measure cognitive impairment was remotely performed by 56 participants from the EverythingALS Speech Study. As part of the study, participants (ALS and non-ALS) were asked to describe weekly one picture from a pool of many pictures with complex scenes displayed on their computer at home. We analyze the descriptions performed within +/- 60 days from the day the ECAS test was administered and extract different types of linguistic and acoustic features. We input those features into linear regression models to infer 5 ECAS sub-scores and the total score. Speech samples from the picture description are reliable enough to predict the ECAS subs-scores, achieving statistically significant Spearman correlation values between 0.32 and 0.51 for the model's performance using 10-fold cross-validation., Comment: conference paper

Topological excitations or defects such as solitons are ubiquitous throughout physics, supporting numerous interesting phenomena like zero energy modes with exotic statistics and fractionalized charges. In this paper, we study such objects through the lens of symmetry-resolved entanglement entropy. Specifically, we compute the charge-resolved entanglement entropy for a single interval in the low-lying states of the Su-Schrieffer-Heeger model in the presence of topological defects. Using a combination of exact and asymptotic analytical techniques, backed up by numerical analysis, we find that, compared to the unresolved counterpart and to the pure system, a richer structure of entanglement emerges. This includes a redistribution between its configurational and fluctuational parts due to the presence of the defect and an interesting interplay with entanglement equipartition. In particular, in a subsystem that excludes the defect, equipartition is restricted to charge sectors of the same parity, while full equipartition is restored if the subsystem includes the defect, as long as the associated zero mode remains unoccupied. Additionally, by exciting zero modes in the presence of multiple defects, we observe a significant enhancement of entanglement in certain charge sectors, due to charge splitting on the defects. The two different scenarios featuring the breakdown of entanglement equipartition are underlied by a joint mechanism, which we unveil by relating them to degeneracies in the spectrum of the entanglement Hamiltonian. In addition, equipartition is shown to stem from an equidistant entanglement spectrum., Comment: 17 pages, 7 figures and 4 appendices

Identifying a small molecule from its mass spectrum is the primary open problem in computational metabolomics. This is typically cast as information retrieval: an unknown spectrum is matched against spectra predicted computationally from a large database of chemical structures. However, current approaches to spectrum prediction model the output space in ways that force a tradeoff between capturing high resolution mass information and tractable learning. We resolve this tradeoff by casting spectrum prediction as a mapping from an input molecular graph to a probability distribution over molecular formulas. We discover that a large corpus of mass spectra can be closely approximated using a fixed vocabulary constituting only 2% of all observed formulas. This enables efficient spectrum prediction using an architecture similar to graph classification - GrAFF-MS - achieving significantly lower prediction error and orders-of-magnitude faster runtime than state-of-the-art methods.

Subseasonal forecasting -- predicting temperature and precipitation 2 to 6 weeks ahead -- is critical for effective water allocation, wildfire management, and drought and flood mitigation. Recent international research efforts have advanced the subseasonal capabilities of operational dynamical models, yet temperature and precipitation prediction skills remain poor, partly due to stubborn errors in representing atmospheric dynamics and physics inside dynamical models. Here, to counter these errors, we introduce an adaptive bias correction (ABC) method that combines state-of-the-art dynamical forecasts with observations using machine learning. We show that, when applied to the leading subseasonal model from the European Centre for Medium-Range Weather Forecasts (ECMWF), ABC improves temperature forecasting skill by 60-90% (over baseline skills of 0.18-0.25) and precipitation forecasting skill by 40-69% (over baseline skills of 0.11-0.15) in the contiguous U.S. We couple these performance improvements with a practical workflow to explain ABC skill gains and identify higher-skill windows of opportunity based on specific climate conditions.

The classical pattern matching paradigm is that of seeking occurrences of one string - the pattern, in another - the text, where both strings are drawn from an alphabet set $\Sigma$. Assuming the text length is $n$ and the pattern length is $m$, this problem can naively be solved in time $O(nm)$. In Knuth, Morris and Pratt's seminal paper of 1977, an automaton, was developed that allows solving this problem in time $O(n)$ for any alphabet. This automaton, which we will refer to as the {\em KMP-automaton}, has proven useful in solving many other problems. A notable example is the {\em parameterized pattern matching} model. In this model, a consistent renaming of symbols from $\Sigma$ is allowed in a match. The parameterized matching paradigm has proven useful in problems in software engineering, computer vision, and other applications. It has long been suspected that for texts where the symbols are uniformly random, the naive algorithm will perform as well as the KMP algorithm. In this paper we examine the practical efficiency of the KMP algorithm vs. the naive algorithm on a randomly generated text. We analyse the time under various parameters, such as alphabet size, pattern length, and the distribution of pattern occurrences in the text. We do this for both the original exact matching problem and parameterized matching. While the folklore wisdom is vindicated by these findings for the exact matching case, surprisingly, the KMP algorithm works significantly faster than the naive in the parameterized matching case. We check this hypothesis for DNA texts, and observe a similar behaviour as in the random text. We also show a very structured case where the automaton is much more efficient.

Entanglement measures constitute powerful tools in the quantitative description of quantum many-body systems out of equilibrium. We study entanglement in the current-carrying steady state of a paradigmatic one-dimensional model of noninteracting fermions at zero temperature in the presence of a scatterer. We show that disjoint intervals located on opposite sides of the scatterer, and within similar distances from it, maintain volume-law entanglement regardless of their separation, as measured by their fermionic negativity and coherent information. The mutual information of the intervals, which quantifies the total correlations between them, follows a similar scaling. Interestingly, this scaling entails in particular that if the position of one of the intervals is kept fixed, then the correlation measures depend non-monotonically on the distance between the intervals. By deriving exact expressions for the extensive terms of these quantities, we prove their simple functional dependence on the scattering probabilities, and demonstrate that the strong long-range entanglement is generated by the coherence between the transmitted and reflected parts of propagating particles within the bias-voltage window. The generality and simplicity of the model suggest that this behavior should characterize a large class of nonequilibrium steady states., Comment: 5 pages, 3 figures + Supplemental Material. v2: Published version, 10+10 pages, 3+2 figures; the discussion of logarithmic corrections was removed, and is now elaborated separately in arXiv:2310.16901

The PHENIX collaboration presents a systematic study of $\pi^0$ production from $p$$+$$p$, $p$$+$Al, $p$$+$Au, $d$$+$Au, and $^{3}$He$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV. Measurements were performed with different centrality selections as well as the total inelastic, 0%--100%, selection for all collision systems. For 0%--100% collisions, the nuclear modification factors, $R_{xA}$, are consistent with unity for $p_T$ above 8 GeV/$c$, but exhibit an enhancement in peripheral collisions and a suppression in central collisions. The enhancement and suppression characteristics are similar for all systems for the same centrality class. It is shown that for high-$p_T$-$\pi^0$ production, the nucleons in the $d$ and $^3$He interact mostly independently with the Au nucleus and that the counter intuitive centrality dependence is likely due to a physical correlation between multiplicity and the presence of a hard scattering process. These observations disfavor models where parton energy loss has a significant contribution to nuclear modifications in small systems. Nuclear modifications at lower $p_T$ resemble the Cronin effect -- an increase followed by a peak in central or inelastic collisions and a plateau in peripheral collisions. The peak height has a characteristic ordering by system size as $p$$+$Au $>$ $d$$+$Au $>$ $^{3}$He$+$Au $>$ $p$$+$Al. For collisions with Au ions, current calculations based on initial state cold nuclear matter effects result in the opposite order, suggesting the presence of other contributions to nuclear modifications, in particular at lower $p_T$., Comment: 554 authors from 81 institutions, 21 pages, 13 figures, and 3 tables. Data from 2008, 2014, and 2015. v2 is version accepted for publication in Physical Review C. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

Subseasonal forecasting of the weather two to six weeks in advance is critical for resource allocation and advance disaster notice but poses many challenges for the forecasting community. At this forecast horizon, physics-based dynamical models have limited skill, and the targets for prediction depend in a complex manner on both local weather variables and global climate variables. Recently, machine learning methods have shown promise in advancing the state of the art but only at the cost of complex data curation, integrating expert knowledge with aggregation across multiple relevant data sources, file formats, and temporal and spatial resolutions. To streamline this process and accelerate future development, we introduce SubseasonalClimateUSA, a curated dataset for training and benchmarking subseasonal forecasting models in the United States. We use this dataset to benchmark a diverse suite of models, including operational dynamical models, classical meteorological baselines, and ten state-of-the-art machine learning and deep learning-based methods from the literature. Overall, our benchmarks suggest simple and effective ways to extend the accuracy of current operational models. SubseasonalClimateUSA is regularly updated and accessible via the https://github.com/microsoft/subseasonal_data/ Python package.