arXiv subjects

Omri Lesser

Publications and source records attributed to Omri Lesser.

At least 19 recordsLinked to original sources

arXiv2026

Trial wavefunction for fractional quantum spin Hall insulators

Fermions with opposite spins occupying half-filled conjugate Chern bands exhibit interaction physics distinct from their multi-component Landau-level counterparts with the same chirality. This is largely due to unavoidable inter-species collisions that preclude the Halperin-type wavefunctions available in multi-component Landau levels. In this work, we propose and evaluate a variational wavefunction for a fractional quantum spin Hall state with Z_4 topological order in a pair of conjugate Landau levels. This Z_4 topological order has previously been shown to be the minimal topological order compatible with charge conservation, $S_z$ conservation, time-reversal symmetry, and the fractional spin Hall conductance 1/2 suggested by previous twisted MoTe$_2$ experiments. Our construction is based on the condensation of an anyonic exciton formed by the neutral fermionic excitations in a decoupled pair of Moore-Read Pfaffian state and its conjugate. By coupling the chiral and anti-chiral Ising conformal field theories associated with the two spin species, we introduce a variational mass parameter in the Z_4 trial wavefunction that captures the inter-spin-species s-wave pairing of composite fermions alongside the intra-spin-species p-wave pairing. We assess the energetics of this trial state using Monte Carlo sampling on a spherical geometry. Because the coupled state intrinsically involves Landau-level mixing, we explicitly evaluate the resulting kinetic energy penalty. Our phase diagram reveals that the proposed Z_4 state becomes energetically favorable in a sizable region of parameter space, over both the decoupled pair of conjugate Pfaffian states and an alternative exciton condensate state. These results provide a concrete microscopic wavefunction realization of this Z_4 fractional quantum spin Hall phase, and propose a route to constructing additional families of such states.

cond-mat.str-el↗

arXiv2026

Charting the emergent low-dimensional manifold of quantum materials

The periodic table of elements transformed chemistry by revealing simple organizing principles underlying atomic behavior. Despite decades of effort, no analogous framework has emerged for crystalline materials -- their microscopic complexity and vast configurational space have defied reduction to fundamental organizing principles. Current databases catalog thousands of synthesized materials, but extracting predictive, interpretable models from this wealth of data remains a formidable challenge. Here we demonstrate that the materials landscape possesses a hidden geometric organization that can be unveiled through unsupervised nonlinear dimensionality reduction. Applying differential geometry techniques to the Inorganic Crystal Structure Database (ICSD), we reveal that just a few combinations of microscopic descriptors capture the vast majority of variance in material properties. This low-dimensional embedding autonomously segregates superconductors from ordinary materials and further distinguishes superconducting families in ways that transcend chemical similarity alone. Remarkably, the discovered geometric organization directly governs critical temperatures ($T_c$) across diverse superconducting families, enabling accurate $T_c$ predictions without any knowledge of the pairing mechanism. Our approach uncovers emergent organizing principles that control macroscopic quantum behavior, offering a new paradigm in how we build models of complex quantum materials directly from experimental data.

cond-mat.supr-con↗

arXiv2026

Learning from almost nothing: How neural networks survive heavy input corruption

Learning from imperfect data is a central theme in machine learning, connecting practical questions of robustness to fundamental questions of learnability. Here we examine attribute noise: learning from corrupted inputs while keeping the labels intact, a setting that has received considerably less analytical attention than its label-noise counterpart. We consider two types of corruption models: additive noise and replacement noise. Through experiments with multi-layer perceptrons (MLPs) on corrupted classification datasets, we find that neural networks remain robust, maintaining well-above-chance accuracy even when inputs are >90% corrupted -- far beyond human recognition. To understand this robustness, we analyze infinite-width networks in the heavy-corruption regime using a mean-field-inspired approach and derive a leading-order decision rule for the classification outcome: the network implements a prototype rule, the nearest-class-mean, assigning each test point to the class whose training-set average it most closely resembles. This leading-order decision rule is universal across a broad range of MLP architectures, holding for any depth, as well as a wide class of activation functions and noise distributions. The same centroid mechanism closely matches finite-width network behavior in our experiments and provides an interpretable and analytically tractable account of why learning can succeed even when individual training examples carry almost no signal.

cs.LG↗

arXiv2026

Graphlet Histogram Representation Database of Inorganic Crystals

Machine learning models for materials property prediction increasingly rely on representations learned end-to-end from large density-functional-theory databases, limiting their applicability when only scarce experimental data are available. Domain-knowledge-driven representations precomputed from crystal structures alone offer a data-efficient, interpretable alternative, but existing approaches capture at most composition or bonding connectivity and discard local structural geometry. Here, we present Graphlet-MP, a database of graphlet histogram representations for 149,082 inorganic crystals from the Materials Project (MP). Seventy-nine distributions describe each material over three hierarchical graphlet orders: atomic sites, bonded pairs, and bond-angle triplets, extracted via screened Voronoi tessellation from the crystallographic information file. We provide a complete technical specification of the representation, an Earth Mover's Distance metric for comparing materials in this space, and the full precomputed database. An accompanying open-source codebase enables users to generate graphlet histograms for arbitrary crystal structures, including experimentally determined ones, and to extend the database to new materials or target properties.

cond-mat.mtrl-sci↗

arXiv2026

Competing nonlinearities, criticality, and order-to-chaos transition in deep networks

Deep neural networks owe their expressive power to nonlinear activation functions. The effective field theory of signal propagation at initialization reveals a few distinct universality classes of activations that exhibit different depth scaling. Tuning across these, especially with analytical control, is an open problem. We show that a statistical mixture of activations, where each neuron independently and randomly draws its activation from a two-component distribution with mixing fraction $p$, provides a new mechanism for a continuous phase transition. Applied to a mixture of Tanh and Swish, the transition is sharp in the depth scaling of the preactivation variance, separating a variance-collapsing from a variance-inflating phase; at $p_c$, the network acquires statistical scale invariance, with depth-independent variance, without sacrificing smoothness. This resolves a longstanding tension, where scale-invariant propagation has previously required the non-smooth ReLU family, rendering such networks ill-suited to curvature-based optimizers, physics-informed architectures, and neural-network quantum states. We corroborate the transition through variance propagation, parallel and perpendicular susceptibilities, and Lyapunov exponents. Training multilayer perceptrons on real datasets reveals non-monotonic test performance as a function of $p$, with an optimum near the theoretically predicted $p_c$, confirming that the initialization-level transition has direct consequences for learned representations. The quenched activation disorder acts as a structural regularizer, suppressing memorization of corrupted labels while preserving generalization. Our framework establishes statistical activation mixtures as a controlled tool for navigating the phase diagram of deep network universality classes.

cond-mat.dis-nn↗

arXiv2026

Vortex-parity-controlled diode effect in Corbino topological Josephson junctions

Nonreciprocal supercurrents in Josephson junctions have recently emerged as a sensitive tool for investigating broken symmetries in superconducting quantum materials. Here, we report an even-odd Josephson diode effect (JDE) in Corbino-geometry junctions fabricated on the pristine surface of a bulk-insulating three-dimensional topological insulator (3DTI). We find that the diode polarity, which indicates the preferred direction of supercurrent flow, robustly alternates its sign depending on the parity (even or odd) of the enclosed vortex number. This behavior is absent in two key control devices: a non-topological graphene Corbino Josephson junction and a 3DTI-based linear Josephson junction. These results indicate that the polarity-tunable JDE is intrinsically linked to the unique combination of the proximitized topological superconductivity in the 3DTI surface and the Corbino device's closed-loop geometry. Our theoretical modeling attributes the observed sign change in diode polarity to the alternating sign of periodic boundary conditions in topological superconductors, supporting the interpretation that the vortex-parity-controlled JDE is a direct manifestation of the underlying Andreev bound state topology associated with the presence of non-Abelian anyons in the vortices.

cond-mat.supr-con↗

arXiv2026

Theory of reentrant superconductivity in Corbino Josephson junctions

Josephson junctions made of conventional superconductors display Fraunhofer-like oscillations of the critical current as a function of the threaded magnetic flux. When the superconductors are deposited on the surface of a three-dimensional topological insulator, this pattern is slightly modified due to the presence of chiral Majorana modes. Here we calculate the critical current of a Corbino Josephson junction, where the fluxoid becomes quantized and the superconducting phase has an integer winding. We discover that circular junctions exhibit similar behavior in both topologically trivial and non-trivial scenarios, while non-circular junctions demonstrate a remarkable distinction. Using a simple analytical model, we show that these non-circular junctions exhibit reentrant superconductivity with a period related to their number of corners, and numerically we find that this period is halved in the topological case. The period halving may help establish the existence of topological superconductivity in hybrid topological insulator-superconductor junctions.

cond-mat.mes-hall↗

arXiv2025

Electron-affinity difference distributions as an organizing principle for superconductivity, enabling the discovery of PtPb$_3$Bi

Predicting the superconducting transition temperature ($T_c$) from crystal structure and composition remains a central challenge in condensed-matter physics, reflecting the absence of a broadly predictive framework connecting microscopic bonding to macroscopic quantum behavior. Here, we introduce $\mathcal{GP}$-$T_c$, an interpretable, structure- and chemistry-aware Gaussian process model that enables uncertainty-quantified $T_c$ prediction from experimentally accessible inputs. By encoding local bonding environments as graphlet histograms, we find that the predictive space collapses to a compact set of descriptors: the distribution of electron-affinity (EA) differences between neighboring atoms, together with interatomic distances and simple elemental features, suffices to predict $T_c$ across disparate superconducting families---identifying an overlooked chemical control parameter that underscores the essential role of local structure beyond composition-only approaches. Our results demonstrate that the EA differences serves as an accessible window into electronic structure providing a mechanism-agnostic physical basis that captures $T_c$ across conventional and unconventional families, including doped charge transfer insulators. $\mathcal{GP}$-$T_c$ reproduces the experimentally reported $T_c$ range of the infinite-layer nickelate Nd$_{0.8}$Sr$_{0.2}$NiO$_2$, and we predict and experimentally confirm superconductivity in stoichiometric PtPb$_3$Bi ($T_c \approx 3$~K). To facilitate broad community use, $\mathcal{GP}$-$T_c$ is made available through a web interface for crystal-structure-based prediction, and the same framework identifies additional high-priority superconducting candidates---including SrNiO$_2$ and K(PRh)$_2$---that provide concrete targets for ongoing and future experimental exploration.

cond-mat.supr-con↗

arXiv2025

Melting point depression of charge density wave in 1T-TiSe$_2$ due to size effects

Classical nucleation theory predicts size-dependent nucleation and melting due to surface and confinement effects at the nanoscale. In correlated electronic states, observation of size-dependent nucleation and melting is rarely reported, likely due to the extremely small length scales necessary to observe such effects for electronic states. Here, using 1T-TiSe$_2$ nanoflakes as a prototypical two-dimensional (2D) charge density wave (CDW) system, we perform in-situ cryogenic electron microscopy with temperature down to 20 K and observe size-dependent nucleation and melting of CDWs. Specifically, we observe a melting point depression of CDW for 1T-TiSe$_2$ flakes with lateral sizes less than 100 nm. By fitting experimental data to a Ginzburg-Landau model, we estimate a zero-temperature correlation length of 10--50 nm, which matches the reported CDW domain size for 1T-TiSe$_2$. As the flake size approaches the correlation length, the divergence of the CDW correlation length near the transition is cut off by the finite flake size, limiting long-range order and thereby lowering the transition temperature. For very small flakes whose size is close to the correlation length, we also observe absence of CDWs, as predicted by the model. We thus show that an electronic phase transition follows classical nucleation theory.

cond-mat.mtrl-sci↗

arXiv2025

Emblems of pair density waves: dual identity of topological defects and their transport signatures

The pair density wave (PDW) exemplifies intertwined orders in strongly correlated systems. A recent discovery of superconductivity in a quarter-metal state offers the first experimental system where a pure PDW without uniform superconductivity is suspected, offering a unique opportunity to examine the consequences of intertwined orders. A pure two-dimensional PDW supports an unusual fractional excitation as its topological defect (TD). A TD simultaneously winds the phase of the Cooper pair and distorts the amplitude modulation -- a dual role reflecting its intertwined character. As a vortex, a TD carries fractional vorticity of $\frac{1}{3} h/2e$, whose movement would cause resistance. As a crystalline defect, a TD can be sourced by charge disorder in the system. We show that experimentally observed resistive switching can originate from mobile TDs, while a small magnetic field will restore zero resistance by blocking their motion. The resulting resistive state exhibits extreme anisotropy and a Hall response, with the Hall angle determined by the angle between the current and the TD's Burgers vector. These features will serve as confirmation of the dual identity of topological defects as emblems of PDW order.

cond-mat.supr-con↗

arXiv2025

Gaplessness from disorder and quantum geometry in gapped superconductors

It is well known that disorder can induce low-energy Andreev bound states in a sign-changing, but fully gapped, superconductor at $\pi-$junctions. Generically, these excitations are localized. Starting from a superconductor with a sign-changing and nodeless order parameter in the clean limit, here we demonstrate a mechanism for increasing the localization length associated with the low-energy Andreev bound states at a fixed disorder strength. We find that the Fubini-Study metric associated with the electronic Bloch wavefunctions controls the localization length and the hybridization between bound states localized at distinct $\pi-$junctions. We present results for the inverse participation ratio, superfluid stiffness, site-resolved and disorder-averaged spectral functions as a function of increasing Fubini-Study metric, which indicate an increased tendency towards delocalization. The low-energy properties resemble those of a dirty nodal superconductor with gapless Bogoliubov excitations. We place these results in the context of recent experiments in moire graphene superconductors.

cond-mat.supr-con↗

arXiv2024

Current Flow in Topological Insulator Josephson Junctions due to Imperfections

Recent experiments on planar superconductor-topological insulator-superconductor (S-TI-S) junctions, e.g., in Corbino geometry, have reported low-temperature nonzero Josephson currents in states with integer fluxoid (flux) induced in the junction by a perpendicular magnetic field. This effect was discussed in connection with Majorana zero modes localized in Josephson vortices of such junctions. Here, we provide an explanation for this phenomenon, attributing it to imperfections. We focus on the ``atomic" limit in which the low-energy bound states of different vortices do not overlap. In this limit, we can associate the nonvanishing critical current with the irregularities, e.g., in the junction's width. The low-temperature contribution to the current is provided by the bound states with low but nonzero energy. We also propose clear experimental tests based on microwave spectroscopy, revealing distinctive selection rules for vortex transitions.

cond-mat.mes-hall↗

arXiv2024

Electron Interference as a Probe of Majorana Zero Modes

Detecting Majorana zero modes (MZMs) in topological superconductors remains challenging, as localized non-topological states can mimic MZM signatures. Here, we propose electron interferometry by non-local transport measurements as a definitive probe to distinguish MZMs from non-topological states. We develop an analytical minimal model showing that interference via two MZMs exhibits a robust pattern, in contrast to a non-topological system. We then numerically confirm this using various topological superconductor models. We find that MZMs are characterized by an interference pattern that is insensitive to various perturbations, such as electrostatic gate potential, and resilient to disorder. Our proposed interferometry approach offers an experimentally accessible means to detect MZMs, probing their underlying nature through a universal response.

cond-mat.mes-hall↗

arXiv2023

Josephson junction arrays as a platform for topological phases of matter

Two-dimensional arrays of superconductors separated by normal metallic regions exhibit rich phenomenology and a high degree of controllability. We establish such systems as platforms for topological phases of matter, and in particular chiral topological superconductivity. We propose and theoretically analyze several minimal models for this chiral phase based on commonly available superconductor-semiconductor heterostructures. The topological transitions can be adjusted using a time-reversal-symmetry breaking knob, which can be activated by controlling the phases in the islands, introducing flux through the system, or applying an in-plane exchange field. We demonstrate transport signatures of the chiral topological phase that are unlikely to be mimicked by local non-topological effects. The flexibility and tunability of our platforms, along with the clear-cut experimental fingerprints, make for a viable playground for exploring chiral superconductivity in two dimensions.

cond-mat.mes-hall↗

arXiv2022

One-dimensional topological superconductivity based entirely on phase control

Topological superconductivity in one dimension requires time-reversal symmetry breaking, but at the same time it is hindered by external magnetic fields. We offer a general prescription for inducing topological superconductivity in planar superconductor-normal-superconductor-normal-superconductor (SNSNS) Josephson junctions without applying any magnetic fields on the junctions. Our platform relies on two key ingredients: the three parallel superconductors form two SNS junctions with phase winding, and the Fermi velocities for the two spin branches transverse to the junction must be different from one another. The two phase differences between the three superconductors define a parameter plane which includes large topological regions. We analytically derive the critical curves where the topological phase transitions occur, and corroborate the result with a numerical calculation based on a tight-binding model. We further propose material platforms with unequal Fermi velocities, establishing the experimental feasibility of our approach.

cond-mat.mes-hall↗

arXiv2022

Proximity-Induced Superconductivity in Epitaxial Topological Insulator/Graphene/Gallium Heterostructures

The introduction of superconductivity to the Dirac surface states of a topological insulator leads to a topological superconductor, which may support topological quantum computing through Majorana zero modes. The development of a scalable material platform is key to the realization of topological quantum computing. Here we report on the growth and properties of high-quality (Bi,Sb)2Te3/graphene/gallium heterostructures. Our synthetic approach enables atomically sharp layers at both hetero-interfaces, which in turn promotes proximity-induced superconductivity that originates in the gallium film. A lithography-free, van der Waals tunnel junction is developed to perform transport tunneling spectroscopy. We find a robust, proximity-induced superconducting gap formed in the Dirac surface states in 5-10 quintuple-layer (Bi,Sb)2Te3/graphene/gallium heterostructures. The presence of a single Abrikosov vortex, where the Majorana zero modes are expected to reside, manifests in discrete conductance changes. The present material platform opens up opportunities for understanding and harnessing the application potential of topological superconductivity.

cond-mat.mes-hall↗

arXiv2022

Renormalization-group-inspired neural networks for computing topological invariants

We show that artificial neural networks (ANNs) can, to high accuracy, determine the topological invariant of a disordered system given its two-dimensional real-space Hamiltonian. Furthermore, we describe a "renormalization-group" (RG) network, an ANN which converts a Hamiltonian on a large lattice to another on a small lattice while preserving the invariant. By iteratively applying the RG network to a "base" network that computes the Chern number of a small lattice of set size, we are able to process larger lattices without re-training the system. We therefore show that it is possible to compute real-space topological invariants for systems larger than those on which the network was trained. This opens the door for computation times significantly faster and more scalable than previous methods.

cond-mat.dis-nn↗

arXiv2021

Majorana zero modes induced by superconducting phase bias

Majorana zero modes in condensed matter systems have been the subject of much interest in recent years. Their non-Abelian exchange statistics, making them a unique state of matter, and their potential applications in topological quantum computation, earned them attention from both theorists and experimentalists. It is generally understood that in order to form Majorana zero modes in quasi-one-dimensional topological insulators, time-reversal symmetry must be broken. The straightforward mechanisms for doing so -- applying magnetic fields or coupling to ferromagnets -- turned out to have many unwanted side effects, such as degradation of superconductivity and the formation of sub-gap states, which is part of the reason Majorana zero modes have been eluding direct experimental detection for a long time. Here we review several proposal that rely on controlling the phase of the superconducting order parameter, either as the sole mechanism for time-reversal-symmetry breaking, or as an additional handy knob used to reduce the applied magnetic field. These proposals hold practical promise to improve Majorana formation, and they shed light on the physics underlying the formation of the topological superconducting state.

cond-mat.mes-hall↗