A Holographic Entanglement Entropy at Spi

Defining finite entanglement entropy for a subregion in quantum field theory requires the introduction of two logically independent scales: an IR scale that controls the size of the subregion, and a UV cut-off. In AdS/CFT, the IR scale is the AdS lengthscale, the UV cut-off is the bulk radial cut-off, and the subregion is specified by dimensionless angles. This is the data that determines Ryu-Takayanagi surfaces and their areas in AdS/CFT. We argue that in asymptotically flat space there exists the notion of a "spi-subregion" that one can associate to spatial infinity (spi). Even though geometrically quite different from an AdS subregion, this angle data has the crucial feature that it allows an interpretation as a bi-partitioning of spi. Therefore, the area of the RT surface associated to the spi-subregion can be interpreted as the entanglement entropy of the reduced density matrix of the bulk state under this bi-partition, as in AdS/CFT. For symmetric spi-subregions, these RT surfaces are the waists of Asymptotic Causal Diamonds. In empty flat space they reduce to Rindler horizons, and are analogues of the AdS-Rindler horizons of Casini, Huerta \& Myers. We connect these definitions to previous work on minimal surfaces anchored to screens in empty space, but also generalize the discussion to the case where there are black holes in the bulk. The phases of black hole RT surfaces as the spi-subregion is varied, naturally connect with those of black holes (small and large) in AdS. A key observation is that the radial cut-off is associated to an IR scale in flat space -- and in fact there are no UV divergences. We argue that this is consistent with previous suggestions that in sub-AdS scales the holographic duality is an IR/IR correspondence and that the degrees of freedom are {\em not} those of a local QFT, but those of long strings. Strings are of course, famously UV finite.Comment: 55 pages, many plot

Exemplar-Free Continual Transformer with Convolutions

Continual Learning (CL) involves training a machine learning model in a sequential manner to learn new information while retaining previously learned tasks without the presence of previous training data. Although there has been significant interest in CL, most recent CL approaches in computer vision have focused on convolutional architectures only. However, with the recent success of vision transformers, there is a need to explore their potential for CL. Although there have been some recent CL approaches for vision transformers, they either store training instances of previous tasks or require a task identifier during test time, which can be limiting. This paper proposes a new exemplar-free approach for class/task incremental learning called ConTraCon, which does not require task-id to be explicitly present during inference and avoids the need for storing previous training instances. The proposed approach leverages the transformer architecture and involves re-weighting the key, query, and value weights of the multi-head self-attention layers of a transformer trained on a similar task. The re-weighting is done using convolution, which enables the approach to maintain low parameter requirements per task. Additionally, an image augmentation-based entropic task identification approach is used to predict tasks without requiring task-ids during inference. Experiments on four benchmark datasets demonstrate that the proposed approach outperforms several competitive approaches while requiring fewer parameters.Comment: Accepted in ICCV 202

Convolutional Prompting meets Language Models for Continual Learning

Continual Learning (CL) enables machine learning models to learn from continuously shifting new training data in absence of data from old tasks. Recently, pretrained vision transformers combined with prompt tuning have shown promise for overcoming catastrophic forgetting in CL. These approaches rely on a pool of learnable prompts which can be inefficient in sharing knowledge across tasks leading to inferior performance. In addition, the lack of fine-grained layer specific prompts does not allow these to fully express the strength of the prompts for CL. We address these limitations by proposing ConvPrompt, a novel convolutional prompt creation mechanism that maintains layer-wise shared embeddings, enabling both layer-specific learning and better concept transfer across tasks. The intelligent use of convolution enables us to maintain a low parameter overhead without compromising performance. We further leverage Large Language Models to generate fine-grained text descriptions of each category which are used to get task similarity and dynamically decide the number of prompts to be learned. Extensive experiments demonstrate the superiority of ConvPrompt and improves SOTA by ~3% with significantly less parameter overhead. We also perform strong ablation over various modules to disentangle the importance of different components.Comment: CVPR 2024 Camera Read

Observation of room temperature gate tunable quantum confinement effect in photodoped junctionless MOSFET

In the pursuit of room temperature quantum hardware, our study introduces a gate voltage tunable quantum wire within a tri-gated n-type junctionless MOSFET. The application of gate voltage alters the parabolic potential well of the tri-gated junctionless MOSFET, enabling modification of the nanowire's potential well profile. In the presence of light, photogenerated electrons accumulate at the center of the junctionless nanowire, aligning with the modified potential well profile influenced by gate bias. These carriers at the center are far from interfaces and experience less interfacial noise. Therefore, such clean photo-doping shows clear, repeatable peaks in current for specific gate biases compared to the dark condition, considering different operating drain-to-source voltages at room temperature. We propose that photodoping-induced subband occupation of gate tunable potential well of the nanowire is the underlying phenomenon responsible for this kind of observation. This study reveals experimental findings demonstrating gate-induced switching from semi-classical to the quantum domain, followed by the optical occupancy of electronic sub-bands at room temperature. We developed a compact model based on the Nonequilibrium Green's function formalism to understand this phenomenon in our illuminated device better. This work reveals the survival of the quantum confinement effect at room temperature in such semi-classical transport.Comment: 12 pages, 6 figure

The consequences of SU(3) colorsingletness, Polyakov Loop and Z(3) symmetry on a quark-gluon gas

Based on quantum statistical mechanics we show that the $SU(3)$ color singlet ensemble of a quark-gluon gas exhibits a $Z(3)$ symmetry through the normaized character in fundamental representation and also becomes equivalent, within a stationary point approximation, to the ensemble given by Polyakov Loop. Also Polyakov Loop gauge potential is obtained by considering spatial gluons along with the invariant Haar measure at each space point. The probability of the normalized character in $SU(3)$ vis-a-vis Polyakov Loop is found to be maximum at a particular value exhibiting a strong color correlation. This clearly indicates a transition from a color correlated to uncorrelated phase or vise-versa. When quarks are included to the gauge fields, a metastable state appears in the temperature range $145\le T({\rm{MeV}}) \le 170$ due to the explicit $Z(3)$ symmetry breaking in the quark-gluon system. Beyond $T\ge 170$ MeV the metastable state disappears and stable domains appear. At low temperature a dynamical recombination of ionized $Z(3)$ color charges to a color singlet $Z(3)$ confined phase is evident along with a confining background that originates due to circulation of two virtual spatial gluons but with conjugate $Z(3)$ phases in a closed loop. We also discuss other possible consequences of the center domains in the color deconfined phase at high temperature.Comment: Version published in J. Phys.

Experimental and theoretical study into interface structure and band alignment of the Cu2Zn1–xCdxSnS4 heterointerface for photovoltaic applications

To improve the constraints of kesterite Cu2ZnSnS4 (CZTS) solar cell, such as undesirable band alignment at p–n interfaces, bandgap tuning, and fast carrier recombination, cadmium (Cd) is introduced into CZTS nanocrystals forming Cu2Zn1–xCdxSnS4 through cost-effective solution-based method without postannealing or sulfurization treatments. A synergetic experimental–theoretical approach was employed to characterize and assess the optoelectronic properties of Cu2Zn1–xCdxSnS4 materials. Tunable direct band gap energy ranging from 1.51 to 1.03 eV with high absorption coefficient was demonstrated for the Cu2Zn1–xCdxSnS4 nanocrystals with changing Zn/Cd ratio. Such bandgap engineering in Cu2Zn1–xCdxSnS4 helps in effective carrier separation at interface. Ultrafast spectroscopy reveals a longer lifetime and efficient separation of photoexcited charge carriers in Cu2CdSnS4 (CCTS) nanocrystals compared to that of CZTS. We found that there exists a type-II staggered band alignment at the CZTS (CCTS)/CdS interface, from cyclic voltammetric (CV) measurements, corroborated by first-principles density functional theory (DFT) calculations, predicting smaller conduction band offset (CBO) at the CCTS/CdS interface as compared to the CZTS/CdS interface. These results point toward efficient separation of photoexcited carriers across the p–n junction in the ultrafast time scale and highlight a route to improve device performances

From Atoms to Cells:Multiscale Modeling of LiNi_xMn_yCo_zO₂Cathodes for Li-Ion Batteries

First-generation cathodes for commercial lithium-ion batteries are based on layered transition-metal oxides. Research on ternary compounds, such as LiCoO2, evolved into mixed-metal systems, notably Li(Ni,Mn,Co)O2 (NMCs), which allows significant tuning of the physical properties. Despite their widespread application in commercial devices, the fundamental understanding of NMCs is incomplete. Here, we review the latest insights from multiscale modeling, bridging between the redox phenomena that occur at an atomistic level to the transport of ions and electrons across an operating device. We discuss changes in the electronic and vibrational structures through the NMC compositional space and how these link to continuum models of electrochemical charge-discharge cycling. Finally, we outline the remaining challenges for predictive models of high-performance batteries, including capturing the relevant device bottlenecks and chemical degradation processes, such as oxygen evolution. </p

No magic bullet: limiting in-school transmission in the face of variable SARS-CoV-2 viral loads

In the face of a long-running pandemic, understanding the drivers of ongoing SARS-CoV-2 transmission is crucial for the rational management of COVID-19 disease burden. Keeping schools open has emerged as a vital societal imperative during the pandemic, but in-school transmission of SARS-CoV-2 can contribute to further prolonging the pandemic. In this context, the role of schools in driving SARS-CoV-2 transmission acquires critical importance. Here we model in-school transmission from first principles to investigate the effectiveness of layered mitigation strategies on limiting in-school spread. We examined the effect of masks and air quality (ventilation, filtration and ionizers) on steady-state viral load in classrooms, as well as on the number of particles inhaled by an uninfected person. The effectiveness of these measures in limiting viral transmission was assessed for variants with different levels of mean viral load (ancestral, Delta, Omicron). Our results suggest that a layered mitigation strategy can be used effectively to limit in-school transmission, with certain limitations. First, poorly designed strategies (insufficient ventilation, no masks, staying open under high levels of community transmission) will permit in-school spread even if some level of mitigation is present. Second, for viral variants that are sufficiently contagious, it may be difficult to construct any set of interventions capable of blocking transmission once an infected individual is present, underscoring the importance of other measures. Our findings provide practical recommendations; in particular, the use of a layered mitigation strategy that is designed to limit transmission, with other measures such as frequent surveillance testing and smaller class sizes (such as by offering remote schooling options to those who prefer it) as needed.National Science Foundationhttps://www.frontiersin.org/articles/10.3389/fpubh.2022.941773/fullPublished versio

Long-term adoption of bed planted conservation agriculture based maize/cotton-wheat system enhances soil organic carbon stabilization within aggregates in the indo-gangetic plains

Sustainability of contemporary crop establishment and management practices is questioned due to soil degradation, higher carbon emission and declining soil productivity. Hence, this study was conducted to address the impacts of conservation agriculture (CA) practices like permanent broad beds (PBB), permanent narrow beds (PNB) and zero tilled flat beds (ZT) with residue retention on soil organic carbon (SOC) protection within aggregates in the Indo-Gangetic Plains (IGP). Compared to conventionally tilled (CT) plots, the total SOC content was ∼27%–33% higher in the CA plots on equivalent mass basis. The soil physical properties, such as soil aggregation and mean weight diameter were considerably improved under the CA practices. The macroaggregates were ∼41, 37% and 27% higher in the PBB with residue (PBB + R), PNB with residue (PNB + R) and ZT with residue (ZT + R) plots (CA plots), respectively, than the CT plots in the surface soil (0–15 cm). The plots under PBB + R had ∼31% higher microaggregates within macroaggregates than the CT plots (24.4 g 100 g−1) soil. An increase in SOC content by ∼72, 55% and 69% was observed in the PBB + R, PNB + R and ZT + R plots over the CT plots in microaggregates within macroaggregates (3.02 Mg ha−1). However, plots under PBB + R, PNB + R and ZT + R had only ∼11, 3% and 23% more SOC within silt + clay fraction, respectively, than CT plots (5.85 Mg ha−1). Thus, SOC stabilization within microaggregates inside macroaggregates was the major mechanism, and not the chemical stabilization within silt + clay, of C sequestration under CA. As aggregate-associated carbon is an ecosystem property that strongly affects organic carbon stabilization, water holding capacity and resistance to erosion, growing maize/cotton–wheat system under PBB + R practice is a viable option for carbon sequestration in the IGP and similar agro-ecologies