@article{14257, abstract = {Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.}, author = {Michalska, Julia M and Lyudchik, Julia and Velicky, Philipp and Korinkova, Hana and Watson, Jake and Cenameri, Alban and Sommer, Christoph M and Amberg, Nicole and Venturino, Alessandro and Roessler, Karl and Czech, Thomas and Höftberger, Romana and Siegert, Sandra and Novarino, Gaia and Jonas, Peter M and Danzl, Johann G}, issn = {1546-1696}, journal = {Nature Biotechnology}, pages = {1051--1064}, publisher = {Springer Nature}, title = {{Imaging brain tissue architecture across millimeter to nanometer scales}}, doi = {10.1038/s41587-023-01911-8}, volume = {42}, year = {2024}, } @unpublished{18689, abstract = {Multiplexed fluorescence microscopy imaging is widely used in biomedical applications. However, simultaneous imaging of multiple fluorophores can result in spectral leaks and overlapping, which greatly degrades image quality and subsequent analysis. Existing popular spectral unmixing methods are mainly based on computational intensive linear models and the performance is heavily dependent on the reference spectra, which may greatly preclude its further applications. In this paper, we propose a deep learning-based blindly spectral unmixing method, termed AutoUnmix, to imitate the physical spectral mixing process. A tranfer learning framework is further devised to allow our AutoUnmix adapting to a variety of imaging systems without retraining the network. Our proposed method has demonstrated real-time unmixing capabilities, surpassing existing methods by up to 100-fold in terms of unmixing speed. We further validate the reconstruction performance on both synthetic datasets and biological samples. The unmixing results of AutoUnmix achieve a highest SSIM of 0.99 in both three- and four-color imaging, with nearly up to 20% higher than other popular unmixing methods. Due to the desirable property of data independency and superior blind unmixing performance, we believe AutoUnmix is a powerful tool to study the interaction process of different organelles labeled by multiple fluorophores.}, author = {Gallei, Michelle C and Truckenbrodt, Sven M and Kreuzinger, Caroline and Inumella, Syamala and Vistunou, Vitali and Sommer, Christoph M and Tavakoli, Mojtaba and Agudelo Duenas, Nathalie and Vorlaufer, Jakob and Jahr, Wiebke and Randuch, Marek and Johnson, Alexander J and Benková, Eva and Friml, Jiří and Danzl, Johann G}, booktitle = {bioRxiv}, title = {{Super-resolution expansion microscopy in plant roots}}, doi = {10.1101/2024.02.21.581330}, year = {2024}, } @phdthesis{18674, abstract = {Mapping the complex and dense arrangement of cells and their connectivity in brain tissue requires volumetric imaging at nanoscale spatial resolution. While light microscopy excels at visualizing specific molecules and individual cells, achieving dense, synapse-level circuit reconstruction has not been possible with any light microscopy technique. Thus, the goal of my work was to develop image and data analysis pipelines for brain tissue visualization and reconstruction with light microscopy. To achieve dense circuit reconstruction with single-synapse resolution, I developed both conventional and deep-learning-based synapse detection algorithms, as well as connectivity analysis pipelines that integrate synapse detection with volumetric segmentation of brain tissue.}, author = {Lyudchik, Julia}, isbn = { 978-3-99078-051-0}, issn = {2663-337X}, pages = {217}, publisher = {Institute of Science and Technology Austria}, title = {{Image analysis for brain tissue reconstruction with super-resolution light microscopy}}, doi = {10.15479/at:ista:18674}, year = {2024}, } @phdthesis{18681, author = {Tavakoli, Mojtaba}, isbn = {978-3-99078-048-0}, issn = {2663-337X}, pages = {230}, publisher = {Institute of Science and Technology Austria}, title = {{Developing molecular and structural tools for studying brain architecture with super resolution expansion microscopy. LICONN: Molecularly-informed connectomics reconstruction with light microscopy}}, doi = {10.15479/at:ista:18681}, year = {2024}, } @unpublished{18677, abstract = {The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution with dense cellular labeling. Light microscopy is uniquely positioned to visualize specific molecules but dense, synapse-level circuit reconstruction by light microscopy has been out of reach due to limitations in resolution, contrast, and volumetric imaging capability. Here we developed light-microscopy based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning based segmentation and analysis of connectivity, thus directly incorporating molecular information in synapse-level brain tissue reconstructions. LICONN will allow synapse-level brain tissue phenotyping in biological experiments in a readily adoptable manner.}, author = {Tavakoli, Mojtaba and Lyudchik, Julia and Januszewski, Michał and Vistunou, Vitali and Agudelo Duenas, Nathalie and Vorlaufer, Jakob and Sommer, Christoph M and Kreuzinger, Caroline and Oliveira, Bárbara and Cenameri, Alban and Novarino, Gaia and Jain, Viren and Danzl, Johann G}, booktitle = {bioRxiv}, title = {{Light-microscopy based dense connectomic reconstruction of mammalian brain tissue}}, doi = {10.1101/2024.03.01.582884}, year = {2024}, } @unpublished{18688, abstract = {The human brain has remarkable computational power. It generates sophisticated behavioral sequences, stores engrams over an individual’s lifetime, and produces higher cognitive functions up to the level of consciousness. However, so little of our neuroscience knowledge covers the human brain, and it remains unknown whether this organ is truly unique, or is a scaled version of the extensively studied rodent brain. To address this fundamental question, we determined the cellular, synaptic, and connectivity rules of the hippocampal CA3 recurrent circuit using multicellular patch clamp-recording. This circuit is the largest autoassociative network in the brain, and plays a key role in memory and higher-order computations such as pattern separation and pattern completion. We demonstrate that human hippocampal CA3 employs sparse connectivity, in stark contrast to neocortical recurrent networks. Connectivity sparsifies from rodents to humans, providing a circuit architecture that maximizes associational power. Unitary synaptic events at human CA3–CA3 synapses showed both distinct species-specific and circuit-dependent properties, with high reliability, unique amplitude precision, and long integration times. We also identify differential scaling rules between hippocampal pathways from rodents to humans, with a moderate increase in the convergence of CA3 inputs per cell, but a marked increase in human mossy fiber innervation. Anatomically guided full-scale modeling suggests that the human brain’s sparse connectivity, expanded neuronal number, and reliable synaptic signaling combine to enhance the associative memory storage capacity of CA3. Together, our results reveal unique rules of connectivity and synaptic signaling in the human hippocampus, demonstrating the absolute necessity of human brain research and beginning to unravel the remarkable performance of our autoassociative memory circuits.}, author = {Watson, Jake F. and Vargas-Barroso, Victor and Morse-Mora, Rebecca J. and Navas-Olive, Andrea and Tavakoli, Mojtaba and Danzl, Johann G and Tomschik, Matthias and Rössler, Karl and Jonas, Peter M}, booktitle = {bioRxiv}, title = {{Human hippocampal CA3 uses specific functional connectivity rules for efficient associative memory}}, doi = {10.1101/2024.05.02.592169}, year = {2024}, } @phdthesis{17133, abstract = {An ideal quantum computer relies on qubits capable of performing fast gate operations and maintaining strong interconnections while preserving their quantum coherence. Since the inception of experimental eforts toward building a quantum computer, the community has faced challenges in engineering such a system. Among the various methods of implementing a quantum computer, superconducting qubits have shown fast gates close to tens of nanoseconds, with the state-of-the-art reaching a coherence of a few milliseconds. However, achieving simultaneously long lifetimes with fast qubit operations poses an inherent paradox. Qubits with high coherence require isolation from the environment, while fast operation necessitates strong coupling of the qubit. This thesis approaches this issue by proposing the idea of engineering superconducting qubits capable of transitioning between operating in a protected regime, where the qubit is completely isolated from the environment, and coupling to the communication channels as needed. In this direction, we use the geometric superinductor to scan the parameter space of rf-SQUID devices, searching for a regime where we can take the qubit protection to its extreme. This leads us to the inductively shunted transmon (IST) regime, characterized by EJ /EC ≫ 1 and EJ /EL ≫ 1, where the circuit potential exhibits a double well with a large barrier separating the local ground states of each quantum well. In this regime, although it is anticipated that the two quantum wells would be isolated from each other, we observe single fuxon tunneling between them. The interplay of the cavity photons and the fuxon transition forms a rich physical system, containing resonance conditions that allow the preparation of the fuxon ground or excited states. This enables us to study the relaxation rate of such transition and show that it can be as large as 3.6 hours. Dynamically controlling the barrier height between the two quantum wells allows for controllable coupling, which scales exponentially, for a qubit encoded in two fuxon states. The 0-π qubit is one of the very few known superconducting circuit types that ofers exponential protection from both relaxation and dephasing simultaneously. However, this qubit is not exempt from the fact that such protection comes at the expense of complex readout and control. In this thesis, we propose a way to controllably break the circuit symmetry, the key reason for the protection, to momentarily restore the ability to control and manipulate the qubit. An asymmetry in capacitances and inductances in the 0-π circuit is detrimental since they lead to coupling of the protected state to the thermally occupied parasitic mode of the circuit. However, here we try to exploit a controlled asymmetry in Josephson energies and show that this can be used as a tunable coupler between the protected states. In the future, this should allow to perform gate operations by dynamically controlling the asymmetry instead of driving the protected transition with microwave pulses. Therefore, we believe that the proposed method can make the use of protected qubits more practical in experimental realizations of quantum computing.}, author = {Hassani, Farid}, isbn = {978-3-99078-040-4}, issn = {2663-337X}, keywords = {Quantum information, Qubits, Superconducting devices}, pages = {161}, publisher = {Institute of Science and Technology Austria}, title = {{Superconducting qubits capable of dynamic switching between protected and high-speed control regimes}}, doi = {10.15479/at:ista:17133}, year = {2024}, } @article{14852, abstract = {The physical conditions giving rise to high escape fractions of ionizing radiation (LyC fesc) in star-forming galaxies – most likely protagonists of cosmic reionization – are not yet fully understood. Using the VLT/MUSE observations of ∼1400 Ly α emitters at 2.9 < z < 6.7, we compare stacked rest-frame UV spectra of candidates for LyC leakers and non-leakers selected based on their Ly α profiles. We find that the stacks of potential LyC leakers, i.e. galaxies with narrow, symmetric Ly α profiles with small peak separation, generally show (i) strong nebular O iii]λ1666, [Si iii]λ1883, and [C iii]λ1907 +C iii]λ1909 emission, indicating a high-ionization state of the interstellar medium (ISM); (ii) high equivalent widths of He iiλ1640 (∼1 − 3 Å), suggesting the presence of hard ionizing radiation fields; (iii) Si ii*λ1533 emission, revealing substantial amounts of neutral hydrogen off the line of sight; (iv) high C ivλλ1548,1550 to [C iii]λ1907 +C iii]λ1909 ratios (C iv/C iii] ≳0.75) , signalling the presence of low column density channels in the ISM. In contrast, the stacks with broad, asymmetric Ly α profiles with large peak separation show weak nebular emission lines, low He iiλ1640 equivalent widths (≲1 Å), and low C iv/C iii] (≲0.25), implying low-ionization states and high-neutral hydrogen column densities. Our results suggest that C iv/C iii] might be sensitive to the physical conditions that govern LyC photon escape, providing a promising tool for identification of ionizing sources among star-forming galaxies in the epoch of reionization.}, author = {Kramarenko, Ivan and Kerutt, J and Verhamme, A and Oesch, P A and Barrufet, L and Matthee, Jorryt J and Kusakabe, H and Goovaerts, I and Thai, T T}, issn = {1365-2966}, journal = {Monthly Notices of the Royal Astronomical Society}, keywords = {Space and Planetary Science, Astronomy and Astrophysics}, number = {4}, pages = {9853--9871}, publisher = {Oxford University Press}, title = {{Linking UV spectral properties of MUSE Ly α emitters at z ≳ 3 to Lyman continuum escape}}, doi = {10.1093/mnras/stad3853}, volume = {527}, year = {2024}, } @article{18266, abstract = {Matrix games are the most basic model in game theory, and yet robustness with respect to small perturbations of the matrix entries is not fully understood. In this paper, we introduce value positivity and uniform value positivity, two properties that refine the notion of optimality in the context of polynomially perturbed matrix games. The first concept captures how the value depends on the perturbation parameter, and the second consists of the existence of a fixed strategy that guarantees the value of the unperturbed matrix game for every sufficiently small positive parameter. We provide polynomial-time algorithms to check whether a polynomially perturbed matrix game satisfies these properties. We further provide the functional form for a parameterized optimal strategy and the value function. Finally, we translate our results to linear programming and stochastic games, where value positivity is related to the existence of robust solutions.}, author = {Chatterjee, Krishnendu and Oliu-Barton, Miquel and Saona Urmeneta, Raimundo J}, issn = {1526-5471}, journal = {Mathematics of Operations Research}, number = {4}, pages = {2433--3282}, publisher = {Institute for Operations Research and the Management Sciences}, title = {{Value-positivity for matrix games}}, doi = {10.1287/moor.2022.0332}, volume = {50}, year = {2024}, } @article{17047, abstract = {We provide a dynamical study of a model of multiplicative perturbation of a unitary matrix introduced by Fyodorov. In particular, we identify a flow of deterministic domains that bound the spectrum with high probability, separating the outlier from the typical eigenvalues at all sub-critical timescales. These results are obtained under generic assumptions on U that hold for a variety of unitary random matrix models.}, author = {Dubach, Guillaume and Reker, Jana}, issn = {2010-3271}, journal = {Random Matrices: Theory and Applications}, number = {2}, publisher = {World Scientific Publishing}, title = {{Dynamics of a rank-one multiplicative perturbation of a unitary matrix}}, doi = {10.1142/s2010326324500072}, volume = {13}, year = {2024}, } @inproceedings{18891, abstract = {Deep neural networks (DNNs) exhibit a surprising structure in their final layer known as neural collapse (NC), and a growing body of works has currently investigated the propagation of neural collapse to earlier layers of DNNs – a phenomenon called deep neural collapse (DNC). However, existing theoretical results are restricted to special cases: linear models, only two layers or binary classification. In contrast, we focus on non-linear models of arbitrary depth in multi-class classification and reveal a surprising qualitative shift. As soon as we go beyond two layers or two classes, DNC stops being optimal for the deep unconstrained features model (DUFM) – the standard theoretical framework for the analysis of collapse. The main culprit is a low-rank bias of multi-layer regularization schemes: this bias leads to optimal solutions of even lower rank than the neural collapse. We support our theoretical findings with experiments on both DUFM and real data, which show the emergence of the low-rank structure in the solution found by gradient descent.}, author = {Súkeník, Peter and Lampert, Christoph and Mondelli, Marco}, booktitle = {38th Annual Conference on Neural Information Processing Systems}, location = {Vancouver, Canada}, publisher = {Neural Information Processing Systems Foundation}, title = {{Neural collapse versus low-rank bias: Is deep neural collapse really optimal?}}, volume = {37}, year = {2024}, } @phdthesis{18515, abstract = {Understanding the role of evolutionary processes in shaping genetic variation has been a primary goal in evolutionary genetics. In this regard, a key question is how genetically distinct populations evolve in the face of gene flow, thereby generating genetic and phenotypic divergence and reproductive isolation (RI). This requires quantifying the role and relative contributions of prezygotic and postzygotic isolating mechanisms on the reduction of gene exchange between populations, and identifying regions in the genome that mediate RI, which is often polygenic. Further, this needs distinguishing neutral and selected regions in the genome, and discerning how selection influences patterns of neutral divergence. Population structure, defined as any deviation from panmixia, such as geographic distribution, movement and mating patterns of individuals, influences how genetic variation is structured in space and shapes the neutral null model. Availability of large scale spatial genomic datasets now enables us to detect signatures of population structure in genetic data and infer population genetic parameters. Such inferences are crucial and have wide applications in biodiversity, conservation genetics, population management and medical genetics. However, inferences are based on assumptions that do not always match the complex reality, thus leading to erroneous conclusions. Moreover, the role and interaction of heterogeneous population density and dispersal, which are ubiquitous in nature, has been challenging to study owing to their mathematical complexity. In such scenarios, feedback between theory, data and simulations can prove to be useful. In this thesis, I examine the effect of population structure on neutral genetic variation and barriers to gene exchange in hybridising populations, thereby bridging together the fields of spatial population genetics and speciation. Despite being a key concept in speciation, reproductive isolation (RI) lacks a quantitative definition and has been used and measured differently across different fields. Chapter 2 gives a quantitative definition of RI, in terms of the effect of genetic differences on gene flow. We give analytical predictions for RI in a range of scenarios, in terms of effective migration rates for discrete populations and barrier strength for continuous populations. In addition to this, we discuss current measures of RI and their limitations, and propose the need for new measures that combine organismal and genetic perspectives of RI. In chapter 3, I examine the combined effect of assortative mating, sexual selection and viability selection on RI. For this, we consider a polygenic ‘magic’ trait under a mainland-island model. We obtain novel theoretical predictions for molecular divergence in terms of effective migration rates, which bears a simple relationship to measurable fitness components of migrants and various early generation hybrids. We explore the conditions under which local adaptation can be maintained despite maladaptive gene flow and quantify the relative contributions of viability and sexual selection to genome-wide barriers to gene flow. The next two chapters of the thesis focus on a hybrid zone of Antirrhinum majus that consist of two subspecies- the magenta flowered A. m. pseudomajus and the yellow flowered A.m. striatum. Previous studies have suggested that flower colour is target of pollinator mediated selection and is influenced only by few genes. While these regions show high genetic differentiation between the subspecies, the rest of the genome is seen to be well mixed. Chapter 4 examines the effects of heterogeneous population density and leptokurtic dispersal on isolation by distance and the distribution of heterozygosity by focusing on non-flower colour markers. Chapter 5 analyses cline shapes and associations among 6 focal flower colour markers to understand how selection and dispersal maintain this hybrid zone. We see sharp coincident stepped clines at all loci and positive associations throughout the hybrid zone, contrary to the expected patterns from diffusive gene flow. With a novel scheme of inferring dispersal combined with multilocus simulations, we show that stepped clines do not reflect genetic barriers to gene flow, but are rather a result of long-distance migration. This framework allows us to get realistic estimates gene flow and selection and shows how traditional cline analysis may lead to inaccurate conclusions when assumptions of the theory are not met. Overall, this thesis investigates how different features of population structure leave detectable signatures in genetic variation, namely in patterns of isolation by distance, linkage disequilibrium and genetic divergence. It also highlights how effective migration rates provide useful way of analysing polygenic architectures and shed new light into hybrid zones. In doing so, I identify scenarios when simple models become insufficient and suggest possibe directions by combining genetic data with simulations.}, author = {Surendranadh, Parvathy}, issn = {2663-337X}, pages = {219}, publisher = {Institute of Science and Technology Austria}, title = {{Effect of population structure on neutral genetic variation and barriers to gene exchange}}, doi = {10.15479/at:ista:18515}, year = {2024}, } @article{18087, abstract = {We present a theory describing the interaction of structured light, such as light carrying orbital angular momentum, with molecules. The light-matter interaction Hamiltonian we derive is expressed through couplings between spherical gradients of the electric field and the (transition) electric multipole moments of a particle of any nontrivial rotation point group. Our model can therefore accommodate an arbitrary complexity of the molecular and electric field structure, and it can be straightforwardly extended to atoms or nanostructures. Applying this framework to rovibrational spectroscopy of molecules, we uncover the general mechanism of angular momentum exchange between the spin and orbital angular momenta of light, molecular rotation, and its center-of-mass motion. We show that the nonzero vorticity of Laguerre-Gaussian beams can strongly enhance certain rovibrational transitions that are considered forbidden in the case of nonhelical light. We discuss the experimental requirements for the observation of these forbidden transitions in state-of-the-art spatially resolved spectroscopy measurements.}, author = {Maslov, Mikhail and Koutentakis, Georgios and Hrast, Mateja and Heckl, Oliver H. and Lemeshko, Mikhail}, issn = {2643-1564}, journal = {Physical Review Research}, number = {3}, publisher = {American Physical Society}, title = {{Theory of angular momentum transfer from light to molecules}}, doi = {10.1103/physrevresearch.6.033277}, volume = {6}, year = {2024}, } @phdthesis{15020, abstract = {This thesis consists of four distinct pieces of work within theoretical biology, with two themes in common: the concept of optimization in biological systems, and the use of information-theoretic tools to quantify biological stochasticity and statistical uncertainty. Chapter 2 develops a statistical framework for studying biological systems which we believe to be optimized for a particular utility function, such as retinal neurons conveying information about visual stimuli. We formalize such beliefs as maximum-entropy Bayesian priors, constrained by the expected utility. We explore how such priors aid inference of system parameters with limited data and enable optimality hypothesis testing: is the utility higher than by chance? Chapter 3 examines the ultimate biological optimization process: evolution by natural selection. As some individuals survive and reproduce more successfully than others, populations evolve towards fitter genotypes and phenotypes. We formalize this as accumulation of genetic information, and use population genetics theory to study how much such information can be accumulated per generation and maintained in the face of random mutation and genetic drift. We identify the population size and fitness variance as the key quantities that control information accumulation and maintenance. Chapter 4 reuses the concept of genetic information from Chapter 3, but from a different perspective: we ask how much genetic information organisms actually need, in particular in the context of gene regulation. For example, how much information is needed to bind transcription factors at correct locations within the genome? Population genetics provides us with a refined answer: with an increasing population size, populations achieve higher fitness by maintaining more genetic information. Moreover, regulatory parameters experience selection pressure to optimize the fitness-information trade-off, i.e. minimize the information needed for a given fitness. This provides an evolutionary derivation of the optimization priors introduced in Chapter 2. Chapter 5 proves an upper bound on mutual information between a signal and a communication channel output (such as neural activity). Mutual information is an important utility measure for biological systems, but its practical use can be difficult due to the large dimensionality of many biological channels. Sometimes, a lower bound on mutual information is computed by replacing the high-dimensional channel outputs with decodes (signal estimates). Our result provides a corresponding upper bound, provided that the decodes are the maximum posterior estimates of the signal.}, author = {Hledik, Michal}, issn = {2663-337X}, keywords = {Theoretical biology, Optimality, Evolution, Information}, pages = {158}, publisher = {Institute of Science and Technology Austria}, title = {{Genetic information and biological optimization}}, doi = {10.15479/at:ista:15020}, year = {2024}, } @phdthesis{17225, abstract = {This thesis describes the development of an atom interferometer designed to exploit the advantages of utilizing quantum entanglement for enhanced precision measurements beyond the standard quantum limit. While the project remains ongoing, significant progress has been made. A key contribution of this work is the development of Quantrol, an experimental control system leveraging the ARTIQ framework. This software enables precise timing and control without requiring prior knowledge of ARTIQ’s implementation details or coding experience. The interface offers user friendly visual comprehension of the experimental sequence and extended capabilities, allowing researchers to scan variables with a simple click of a mouse. The main proposed project is to implement atom interferometric sequence with squeezed input states inside of a dipole trap generated by a high finesse cavity. The presence of the dipole trap allows one dimensional atomic cloud split while maintaining relatively strong confinement in other directions. We are currently able to trap and cool 87Rb atoms to few micro kelvin temperatures, load them into the dipole trap and state prepare them to be used for squeezing and interferometric sequence.}, author = {Li, Vyacheslav}, issn = {2663-337X}, pages = {79}, publisher = {Institute of Science and Technology Austria}, title = {{Towards a quantum entanglement enhanced atom interferomter}}, doi = {10.15479/at:ista:17225}, year = {2024}, } @phdthesis{18135, abstract = {This thesis consists of two separate parts. In the first part we consider a dilute Fermi gas interacting through a repulsive interaction in dimensions $d=1,2,3$. Our focus is mostly on the physically most relevant dimension $d=3$ and the setting of a spin-polarized (equivalently spinless) gas, where the Pauli exclusion principle plays a key role. We show that, at zero temperature, the ground state energy density of the interacting spin-polarized gas differs (to leading order) from that of the free (i.e. non-interacting) gas by a term of order $a_p^d\rho^{2+2/d}$ with $a_p$ the $p$-wave scattering length of the repulsive interaction and $\rho$ the density. Further, we extend this to positive temperature and show that the pressure of an interacting spin-polarized gas differs from that of the free gas by a now temperature dependent term, again of order $a_p^d\rho^{2+2/d}$. Lastly, we consider the setting of a spin-$\frac{1}{2}$ Fermi gas in $d=3$ dimensions and show that here, as an upper bound, the ground state energy density differs from that of the free system by a term of order $a_s \rho^2$ with an error smaller than $a_s \rho^2 (a_s\rho^{1/3})^{1-\eps}$ for any $\eps > 0$, where $a_s$ is the $s$-wave scattering length of the repulsive interaction. These asymptotic formulas complement the similar formulas in the literature for the dilute Bose and spin-$\frac{1}{2}$ Fermi gas, where the ground state energies or pressures differ from that of the corresponding free systems by a term of order $a_s \rho^2$ in dimension $d=3$. In the spin-polarized setting, the corrections, of order $a_p^3\rho^{8/3}$ in dimension $d=3$, are thus much smaller and requires a more delicate analysis. In the second part of the thesis we consider the Bardeen--Cooper--Schrieffer (BCS) theory of superconductivity and in particular its associated critical temperature and energy gap. We prove that the ratio of the zero-temperature energy gap and critical temperature $\Xi(T=0)/T_c$ approaches a universal constant $\pi e^{-\gamma}\approx 1.76$ in both the limit of high density in dimension $d=3$ and in the limit of weak coupling in dimensions $d=1,2$. This complements the proofs in the literature of this universal behaviour in the limit of weak coupling or low density in dimension $d=3$. Secondly, we prove that the ratio of the energy gap at positive temperature and critical temperature $\Xi(T)/T_c$ approaches a universal function of the relative temperature $T/T_c$ in the limit of weak coupling in dimensions $d=1,2,3$.}, author = {Lauritsen, Asbjørn Bækgaard}, isbn = {978-3-99078-042-8}, issn = {2663-337X}, pages = {353}, publisher = {Institute of Science and Technology Austria}, title = {{Energies of dilute Fermi gases and universalities in BCS theory}}, doi = {10.15479/at:ista:18135}, year = {2024}, } @article{14542, abstract = {It is a remarkable property of BCS theory that the ratio of the energy gap at zero temperature Ξ and the critical temperature Tc is (approximately) given by a universal constant, independent of the microscopic details of the fermionic interaction. This universality has rigorously been proven quite recently in three spatial dimensions and three different limiting regimes: weak coupling, low density and high density. The goal of this short note is to extend the universal behavior to lower dimensions d=1,2 and give an exemplary proof in the weak coupling limit.}, author = {Henheik, Sven Joscha and Lauritsen, Asbjørn Bækgaard and Roos, Barbara}, issn = {1793-6659}, journal = {Reviews in Mathematical Physics}, number = {9}, publisher = {World Scientific Publishing}, title = {{Universality in low-dimensional BCS theory}}, doi = {10.1142/s0129055x2360005x}, volume = {36}, year = {2024}, } @article{14931, abstract = {We prove an upper bound on the ground state energy of the dilute spin-polarized Fermi gas capturing the leading correction to the kinetic energy resulting from repulsive interactions. One of the main ingredients in the proof is a rigorous implementation of the fermionic cluster expansion of Gaudin et al. (1971) [15].}, author = {Lauritsen, Asbjørn Bækgaard and Seiringer, Robert}, issn = {1096-0783}, journal = {Journal of Functional Analysis}, number = {7}, publisher = {Elsevier}, title = {{Ground state energy of the dilute spin-polarized Fermi gas: Upper bound via cluster expansion}}, doi = {10.1016/j.jfa.2024.110320}, volume = {286}, year = {2024}, } @article{18107, abstract = {We consider a dilute fully spin-polarized Fermi gas at positive temperature in dimensions d∈{1,2,3} . We show that the pressure of the interacting gas is bounded from below by that of the free gas plus, to leading order, an explicit term of order adρ2+2/d, where a is the p-wave scattering length of the repulsive interaction and ρ is the particle density. The results are valid for a wide range of repulsive interactions, including that of a hard core, and uniform in temperatures at most of the order of the Fermi temperature. A central ingredient in the proof is a rigorous implementation of the fermionic cluster expansion of Gaudin, Gillespie and Ripka (Nucl. Phys. A, 176.2 (1971), pp. 237–260).}, author = {Lauritsen, Asbjørn Bækgaard and Seiringer, Robert}, issn = {2050-5094}, journal = {Forum of Mathematics, Sigma}, publisher = {Cambridge University Press}, title = {{Pressure of a dilute spin-polarized Fermi gas: Lower bound}}, doi = {10.1017/fms.2024.56}, volume = {12}, year = {2024}, } @phdthesis{18443, abstract = {In [KW06] Kapustin and Witten conjectured that there is a mirror symmetry relation between the hyperkähler structures on certain Higgs bundle moduli spaces. As a consequence, they conjecture an equivalence between categories of BBB and BAA-branes. At the classical level, this mirror symmetry is given by T-duality between semi-flat hyperkähler structures on algebraic integrable systems. In this thesis, we investigate the T-duality relation between hyperkähler structures and the corresponding branes on affine torus bundles. We use the techniques of generalized geometry to show that semi-flat hyperkähler structures are T-dual on algebraic integrable systems. We also describe T-duality for generalized branes. Motivated by Fourier-Mukai transform we upgrade the T-duality between generalized branes to T-duality of submanifolds endowed with U(1)-bundles and connections. This T-duality in the appropriate context specializes to T-duality between BBB and BAA-branes. }, author = {Sisak, Maria A}, issn = {2663-337X}, keywords = {hyperkaehler geometry, branes, mirror symmetry, T-duality}, pages = {178}, publisher = {Institute of Science and Technology Austria}, title = {{T-dual branes on hyperkähler manifolds}}, doi = {10.15479/at:ista:18443}, year = {2024}, }