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Noninvasive optical imaging modalities can probe patient's tissue in 3D and over time generate gigabytes of clinically relevant data per sample. There is a need for AI models to analyze this data and assist clinical workflow. The lack of expert labelers and the large dataset required (>100,000 images) for model training and tuning are the main hurdles in creating foundation models. In this paper we introduce FoundationShift, a method to apply any AI model from computational pathology without retraining. We show our method is more accurate than state of the art models (SAM, MedSAM, SAM-Med2D, CellProfiler, Hover-Net, PLIP, UNI and ChatGPT), with multiple imaging modalities (OCT and RCM). This is achieved without the need for model retraining or fine-tuning. Applying our method to noninvasive in vivo images could enable physicians to readily incorporate optical imaging modalities into their clinical practice, providing real time tissue analysis and improving patient care.

Atomic beams offer measurement capabilities for hot vapors but often require complex, bulky systems, limiting miniaturization. This study explores hot vapors in thin cells (L=30,5 microns) as a simplified analogy to atomic beams. Coherence is maintained only for atoms moving parallel to the cell walls, as wall collisions randomize spin. By filtering non-parallel atoms, we mimic atomic beam behavior and observe the Faraday-Ramsey effect. Rubidium atoms are optically pumped with linearly polarized resonance radiation, evolving in a perpendicular magnetic field and probed via Faraday rotation. We believe that thin cell technology is paving the way for the miniaturization of atomic beam-based sensors., Comment: This PDF submission, intended for consideration by Optica Quantum, combines the main text and Supplementary Information (SI). The document includes 10 pages and 7 figures of the main text, followed by references and then 6 pages with 4 figures of the SI. This arrangement facilitates easy navigation and aligns with journal requirements

We derive exact, universal, closed-form quantum Monte Carlo estimators for finite temperature energy susceptibility and fidelity susceptibility for essentially arbitrary Hamiltonians. We demonstrate how our method can be used to study quantum phase transitions without knowledge of an order parameter and without the need to design system-specific ergodic quantum Monte Carlo update rules by applying it to a class of random models., Comment: 9 pages (5 main, 2 bibliography, 3 supplement), 2 figures

We experimentally study electron transport across a single planar junction between the indium electrode and MnTe altermagnet candidate. We confirm standard Ohmic behavior with strictly linear current-voltage curves above the indium critical field or temperature, although with high, about 100~kOhm, junction resistance. At low temperatures and in zero magnetic field, we observe a well-developed Andreev curve with the pronounced coherence peaks, which cannot be normally expected for these high values of normal junction resistance. The conclusion on the Andreev reflection is also supported by suppression in magnetic field, as well as by universality of the observed behavior for all of the investigated samples. The experimental results can be explained by specifics of Andreev transport through the disordered region at the superconductor-altermagnet interface. Due to a different set of restrictions on the possibility of Andreev reflection, an altermagnet suffers from the presence of disorder less than a normal spin-degenerate metal, so the conductance enhancement is retained throughout the superconducting gap.

Chest X-rays or chest radiography (CXR), commonly used for medical diagnostics, typically enables limited imaging compared to computed tomography (CT) scans, which offer more detailed and accurate three-dimensional data, particularly contrast-enhanced scans like CT Pulmonary Angiography (CTPA). However, CT scans entail higher costs, greater radiation exposure, and are less accessible than CXRs. In this work we explore cross-modal translation from a 2D low contrast-resolution X-ray input to a 3D high contrast and spatial-resolution CTPA scan. Driven by recent advances in generative AI, we introduce a novel diffusion-based approach to this task. We evaluate the models performance using both quantitative metrics and qualitative feedback from radiologists, ensuring diagnostic relevance of the generated images. Furthermore, we employ the synthesized 3D images in a classification framework and show improved AUC in a PE categorization task, using the initial CXR input. The proposed method is generalizable and capable of performing additional cross-modality translations in medical imaging. It may pave the way for more accessible and cost-effective advanced diagnostic tools. The code for this project is available: https://github.com/NoaCahan/X-ray2CTPA ., Comment: preprint, project code: https://github.com/NoaCahan/X-ray2CTPA

Designing distributed systems to have predictable performance under high load is difficult because of resource exhaustion, non-linearity, and stochastic behaviour. Timeliness, i.e., delivering results within defined time bounds, is a central aspect of predictable performance. In this paper, we focus on timeliness using the DELTA-Q Systems Development paradigm (DELTA-QSD, developed by PNSol), which computes timeliness by modelling systems observationally using so-called outcome expressions. An outcome expression is a compositional definition of a system's observed behaviour in terms of its basic operations. Given the behaviour of the basic operations, DELTA-QSD efficiently computes the stochastic behaviour of the whole system including its timeliness. This paper formally proves useful algebraic properties of outcome expressions w.r.t. timeliness. We prove the different algebraic structures the set of outcome expressions form with the different DELTA-QSD operators and demonstrate why those operators do not form richer structures. We prove or disprove the set of all possible distributivity results on outcome expressions. On our way for disproving 8 of those distributivity results, we develop a technique called properisation, which gives rise to the first body of maths for improper random variables. Finally, we also prove 14 equivalences that have been used in the past in the practice of DELTA-QSD. An immediate benefit is rewrite rules that can be used for design exploration under established timeliness equivalence. This work is part of an ongoing project to disseminate and build tool support for DELTA-QSD. The ability to rewrite outcome expressions is essential for efficient tool support., Comment: In Proceedings ICE 2023, arXiv:2308.08920

We present a universal parameter-free quantum Monte Carlo (QMC) algorithm designed to simulate arbitrary spin-$1/2$ Hamiltonians. To ensure the convergence of the Markov chain to equilibrium for every conceivable case, we devise a clear and simple automated protocol that produces QMC updates that are provably ergodic and satisfy detailed balance. We demonstrate the applicability and versatility of our method by considering several illustrative examples, including the simulation of the XY model on a triangular lattice, the toric code, and random $k$-local Hamiltonians. We have made our program code freely accessible on GitHub., Comment: 18 pages, 8 figures

We experimentally investigate charge transport in In-GeTe and In-GeTe-In proximity devices, which are formed as junctions between superconducting indium leads and thick single crystal flakes of $\alpha$-GeTe topological semimetal. We observe nonmonotonic effects of the applied external magnetic field, including reentrant superconductivity in In-GeTe-In Josephson junctions: supercurrent reappears at some finite magnetic field. For a single In-GeTe Andreev junction, the superconducting gap is partially suppressed in zero magnetic field, while the gap is increased nearly to the bulk value for some finite field before its full suppression. We discuss possible reasons for the results obtained, taking into account spin polarization of Fermi arc surface states in topological semimetal $\alpha$-GeTe with a strong spin-orbit coupling. In particular, the zero-field surface state spin polarization partially suppresses the superconductivity, while it is recovered due to the modified spin-split surface state configuration in finite fields. As an alternative possible scenario, the transition into the Fulde-Ferrell-Larkin-Ovchinnikov state is discussed. However, the role of strong spin-orbit coupling in forming the nonmonotonic behavior has not been analyzed for heterostructures in the Fulde-Ferrell-Larkin-Ovchinnikov state, which is crucial for junctions involving GeTe topological semimetal., Comment: One reference has been added

We study gain without inversion due to coherence effects in a Doppler-broadened degenerate three-level system of a rubidium-hydrogen mixture in a miniaturized micron scale custom vapor cell. The cell miniaturization gives rise to collisions of atoms with the walls of the cell. This, combined with the high collision rate with the hydrogen buffer gas allows us to observe gain in the absorption spectra. Furthermore, we analyze the role of cell miniaturization in the evolution of the gain profile. In addition to fundamental interest, the observation of gain without inversion in our miniaturized cells paves the way for applications such as miniaturized lasers without inversion., Comment: 15 pages, 8 figures, 1 table

This paper gives an overview of the unconventional dependence of internal phase differences on the external phase difference in superconductor-normal metal-superconductor (SINIS) and superconductor-superconductor-superconductor (SISIS) tunnel double junctions. The results are obtained within the Ginzburg-Landau (GL) approach that includes boundary conditions for the superconductor order parameter in the presence of a Josephson coupling through interfaces. The boundary conditions are derived within the GL theory and substantiated microscopically. The absence of the one-to-one correspondence between external $\phi$ and internal $\chi_{1,2}$ phase differences in the junctions is shown to occur in two qualitatively different ways, both of which result in the range of $\chi_{1,2}$ reduced and prevent the $4\pi$-periodic current-phase relation $j=j_c\sin\frac{\phi}{2}$. In SINIS junctions, the effect of the supercurrent-induced phase incursion $\varphi$ between the end faces of the central electrode of mesoscopic length $L$ can play a crucial role. In SISIS junctions, there occurs the regime of interchanging modes, which is modified as $L$ decreases. The proximity and pair breaking effects in the double junctions with closely spaced interfaces are addressed., Comment: 22 pages, 7 figures, Contribution for the Annals of Physics special issue in memory of Igor Dzyaloshinskii

The crafting of machine learning (ML) based systems requires statistical control throughout its life cycle. Careful quantification of business requirements and identification of key factors that impact the business requirements reduces the risk of a project failure. The quantification of business requirements results in the definition of random variables representing the system key performance indicators that need to be analyzed through statistical experiments. In addition, available data for training and experiment results impact the design of the system. Once the system is developed, it is tested and continually monitored to ensure it meets its business requirements. This is done through the continued application of statistical experiments to analyze and control the key performance indicators. This book teaches the art of crafting and developing ML based systems. It advocates an "experiment first" approach stressing the need to define statistical experiments from the beginning of the project life cycle. It also discusses in detail how to apply statistical control on the ML based system throughout its lifecycle.

A model is developed for describing the transport of charged colloidal particles in an evaporating sessile droplet on the electrified metal substrate in the presence of a solvent flow. The model takes into account the electric charge of colloidal particles and small ions produced by electrolytic dissociation of the active groups on the colloidal particles and solvent molecules. We employ a system of self-consistent Poisson and Nernst--Planck equations for electric potential and average concentrations of colloidal particles and ions with the appropriate boundary conditions. The fluid dynamics, temperature distribution and evaporation process are described with the Navier--Stokes equations, equations of heat conduction and vapor diffusion in air, respectively. The developed model is used to carry out a first-principles numerical simulation of charged silica colloidal particle transport in an evaporating aqueous droplet. We find that electric double layers can be destroyed by a sufficiently strong fluid flow., Comment: 15 pages, 7 figures

Three-dimensional van der Waals ferromagnet Fe$_3$GeTe$_2$ (FGT) is regarded as a candidate for the magnetic topological nodal line semimetal. We investigate lateral electron transport between two 3~$\mu$m spaced superconducting In leads beneath a thick three-dimensional FGT exfoliated flake. At low 30~mK temperature, we observe Josephson supercurrent that exhibits unusual critical current $I_c$ suppression by the magnetic field $B$. The overall $I_c(B)$ pattern is asymmetric in respect to the B sign. We demonstrate, that the asymmetry is defined by the magnetic field sweep direction, so the $I_c(B)$ pattern is strictly reversed (as $B$ to $-B$ inversion) for the opposite sweeps. We also observe an interplay between maximum and minimum in $I_c(B)$ in normal magnetic fields, while there are fast aperiodic $I_c(B)$ fluctuations for the in-plane ones. These effects can not be expected for homogeneous superconductor-ferromagnet-superconductor junctions, while they are known for Josephson spin valves. The mostly possible scenario for Josephson spin valve realization in FGT is the misalignment of spin polarizations of the Fermi arc surface states and ferromagnetic FGT bulk, but we also discuss possible influence of spin-dependent transport between magnetic domains.

We introduce a method for calculating individual elements of matrix functions. Our technique makes use of a novel series expansion for the action of matrix functions on basis vectors that is memory efficient even for very large matrices. We showcase our approach by calculating the matrix elements of the exponential of a transverse-field Ising model and evaluating quantum transition amplitudes for large many-body Hamiltonians of sizes up to $2^{64} \times 2^{64}$ on a single workstation. We also discuss the application of the method to matrix inverses. We relate and compare our method to the state-of-the-art and demonstrate its advantages. We also discuss practical applications of our method., Comment: 14 pages, 7 figures, 2 tables

Pulmonary embolus (PE) refers to obstruction of pulmonary arteries by blood clots. PE accounts for approximately 100,000 deaths per year in the United States alone. The clinical presentation of PE is often nonspecific, making the diagnosis challenging. Thus, rapid and accurate risk stratification is of paramount importance. High-risk PE is caused by right ventricular (RV) dysfunction from acute pressure overload, which in return can help identify which patients require more aggressive therapy. Reconstructed four-chamber views of the heart on chest CT can detect right ventricular enlargement. CT pulmonary angiography (CTPA) is the golden standard in the diagnostic workup of suspected PE. Therefore, it can link between diagnosis and risk stratification strategies. We developed a weakly supervised deep learning algorithm, with an emphasis on a novel attention mechanism, to automatically classify RV strain on CTPA. Our method is a 3D DenseNet model with integrated 3D residual attention blocks. We evaluated our model on a dataset of CTPAs of emergency department (ED) PE patients. This model achieved an area under the receiver operating characteristic curve (AUC) of 0.88 for classifying RV strain. The model showed a sensitivity of 87% and specificity of 83.7%. Our solution outperforms state-of-the-art 3D CNN networks. The proposed design allows for a fully automated network that can be trained easily in an end-to-end manner without requiring computationally intensive and time-consuming preprocessing or strenuous labeling of the data.We infer that unmarked CTPAs can be used for effective RV strain classification. This could be used as a second reader, alerting for high-risk PE patients. To the best of our knowledge, there are no previous deep learning-based studies that attempted to solve this problem., Comment: 12 pages, 6 figures, 5 tables

We introduce a novel clean-label targeted poisoning attack on learning mechanisms. While classical poisoning attacks typically corrupt data via addition, modification and omission, our attack focuses on data omission only. Our attack misclassifies a single, targeted test sample of choice, without manipulating that sample. We demonstrate the effectiveness of omission attacks against a large variety of learners including deep neural networks, SVM and decision trees, using several datasets including MNIST, IMDB and CIFAR. The focus of our attack on data omission only is beneficial as well, as it is simpler to implement and analyze. We show that, with a low attack budget, our attack's success rate is above 80%, and in some cases 100%, for white-box learning. It is systematically above the reference benchmark for black-box learning. For both white-box and black-box cases, changes in model accuracy are negligible, regardless of the specific learner and dataset. We also prove theoretically in a simplified agnostic PAC learning framework that, subject to dataset size and distribution, our omission attack succeeds with high probability against any successful simplified agnostic PAC learner.

We experimentally investigate the magnetic field dependence of Andreev transport through a region of proximity-induced superconductivity in CoSi topological chiral semimetal. With increasing parallel to the CoSi surface magnetic field, the sharp subgap peaks, associated with Andreev bound states, move together to nearly-zero bias position, while there is only monotonous peaks suppression for normal to the surface fields. The zero-bias $dV/dI$ resistance value is perfectly stable with changing the in-plane magnetic field. As the effects are qualitatively similar for In and Nb superconducting leads, they reflect the properties of proximized CoSi surface. The Andreev states coalescence and stability of the zero-bias $dV/dI$ value with increasing in-plane magnetic field are interpreted as the joined effect of the strong SOC and the Zeeman interaction, known for proximized semiconductor nanowires. We associate the observed magnetic field anisotropy with the recently predicted in-plane polarized spin texture of the Fermi arcs surface states., Comment: final version

Population annealing is a recent addition to the arsenal of the practitioner in computer simulations in statistical physics and beyond that is found to deal well with systems with complex free-energy landscapes. Above all else, it promises to deliver unrivaled parallel scaling qualities, being suitable for parallel machines of the biggest calibre. Here we study population annealing using as the main example the two-dimensional Ising model which allows for particularly clean comparisons due to the available exact results and the wealth of published simulational studies employing other approaches. We analyze in depth the accuracy and precision of the method, highlighting its relation to older techniques such as simulated annealing and thermodynamic integration. We introduce intrinsic approaches for the analysis of statistical and systematic errors, and provide a detailed picture of the dependence of such errors on the simulation parameters. The results are benchmarked against canonical and parallel tempering simulations., Comment: 26 pages, 23 figures

Recently, there is growing interest in integrating alkali vapors with nanoscale photonic structures, such as nano-waveguides, resonators and nanoantennas. Nanoscale confinement of electromagnetic fields may introduce a longitudinal electric field component, giving rise to circularly polarized modes which are essential for diverse applications involving vapor and light, such as chirality and non-reciprocity. Hereby, we have designed, fabricated and characterized a miniaturized vapor cell that is integrated with optical waveguides that are designed to generate a peculiar circular-like polarization. Taking advantage of this phenomenon, we demonstrate a spectral shift in the atomic absorption signatures at varying magnetic fields, and significant isolation between forward and backward propagating waves in our atomic-cladded waveguide. Our results pave the way for the utilization of chip-scale integrated atomic devices in applications such as optical isolation and high spatial resolution magnetometry.

It is demonstrated that the general theory of Casimir and van der Waals forces describes the interaction-induced equilibrium thermodynamic potentials of the damped harmonic oscillator bilinearly coupled to the environment. An extended model for a damped oscillator is suggested along the lines of the general theory of Casimir and van der Waals forces, and the corresponding thermodynamic quantities obtained. While the original model involves a heat bath consisting of a large number of free oscillators having infinitesimal damping functions, the extended model allows any generally admissible frequency and temperature dependent dissipative susceptibilities of the heat bath constituents, influenced by the additional dissipative environmental channels that are not directly linked to the system oscillator. Consequently, the results obtained are applicable to the frequency and temperature dependent damping function of the system oscillator., Comment: 11 pages, slightly extended published version; Contribution for the JETP special issue in honor of I. E. Dzyaloshinskii's 90th birthday

We investigate numerically quasi-steady internal flows in an axially symmetrical evaporating sessile droplet depending on the ratio of substrate to fluid thermal conductivities, fluid volatility, contact angle and droplet size. Temperature distributions and vortex structures are obtained for droplets of 1-hexanol, 1-butanol and ethanol. To this purpose, the hydrodynamics of an evaporating sessile drop, effects of the thermal conduction in the droplet and substrate and diffusion of vapor in air have been jointly taken into account. The equations have been solved by finite element method using ANSYS Fluent. The phase diagrams demonstrating the number and orientation of the vortices as functions of the contact angle and the ratio of substrate to fluid thermal conductivities, are obtained and analyzed for various values of parameters. In particular, influence of gravity on the droplet shape and the effect of droplet size have been considered. We have found that the phase diagrams of highly volatile droplets do not contain a subregion corresponding to a reversed single vortex, and their single-vortex subregion becomes more complex. The phase diagrams for droplets of larger size do not contian subregions corresponding to a regular single vortex and to three vortices. We demonstrate how the single-vortex subregion disappears with a gradual increase of the droplet size., Comment: 13 pages, 3 figures, 2 tables

We study unsteady internal flows in a sessile droplet of capillary size evaporating in constant contact line mode on a heated substrate. Three-dimensional simulations of internal flows in evaporating droplets of ethanol and silicone oil have been carried out. For describing the Marangoni flows we find it necessary to account for the diffusion of vapor in air, the thermal conduction in all three phases and thermal radiation. The equations have been solved numerically by finite element method using ANSYS Fluent. As a result of the simulations, the nonstationary behavior of B\'enard-Marangoni (BM) instabilities is obtained. At the first stage, a flower structure of BM cells near the triple line emerge. For smaller contact angles, the cells grow in size and occupy the central region of the droplet surface. Being closely connected with recent experimental and theoretical studies, the results obtained help to analyze and resolve the associated issues., Comment: 19 pages, 5 figures, 1 table

This review covers experimental results of evaporative lithography and analyzes existing mathematical models of this method. Evaporating droplets and films are used in different fields, such as cooling of heated surfaces of electronic devices, diagnostics in health care, creation of transparent conductive coatings on flexible substrates, and surface patterning. A method called evaporative lithography emerged after the connection between the coffee ring effect taking place in drying colloidal droplets and naturally occurring inhomogeneous vapor flux densities from liquid--vapor interfaces was established. Essential control of the colloidal particle deposit patterns is achieved in this method by producing ambient conditions that induce a nonuniform evaporation profile from the colloidal liquid surface. Evaporative lithography is part of a wider field known as "evaporative-induced self-assembly" (EISA). EISA involves methods based on contact line processes, methods employing particle interaction effects, and evaporative lithography. As a rule, evaporative lithography is a flexible and single-stage process with such advantages as simplicity, low price, and the possibility of application to almost any substrate without pretreatment. Since there is no mechanical impact on the template in evaporative lithography, the template integrity is preserved in the process. The method is also useful for creating materials with localized functions, such as slipperiness and self-healing. For these reasons, evaporative lithography attracts increasing attention and has a number of noticeable achievements at present. We also analyze limitations of the approach and ways of its further development.