@phdthesis{14711,
  abstract     = {In nature, different species find their niche in a range of environments, each with its unique characteristics. While some thrive in uniform (homogeneous) landscapes where environmental conditions stay relatively consistent across space, others traverse the complexities of spatially heterogeneous terrains. Comprehending how species are distributed and how they interact within these landscapes holds the key to gaining insights into their evolutionary dynamics while also informing conservation and management strategies.

For species inhabiting heterogeneous landscapes, when the rate of dispersal is low compared to spatial fluctuations in selection pressure, localized adaptations may emerge. Such adaptation in response to varying selection strengths plays an important role in the persistence of populations in our rapidly changing world. Hence, species in nature are continuously in a struggle to adapt to local environmental conditions, to ensure their continued survival. Natural populations can often adapt in time scales short enough for evolutionary changes to influence ecological dynamics and vice versa, thereby creating a feedback between evolution and demography. The analysis of this feedback and the relative contributions of gene flow, demography, drift, and natural selection to genetic variation and differentiation has remained a recurring theme in evolutionary biology. Nevertheless, the effective role of these forces in maintaining variation and shaping patterns of diversity is not fully understood. Even in homogeneous environments devoid of local adaptations, such understanding remains elusive. Understanding this feedback is crucial, for example in determining the conditions under which extinction risk can be mitigated in peripheral populations subject to deleterious mutation accumulation at the edges of species’ ranges
as well as in highly fragmented populations.

In this thesis we explore both uniform and spatially heterogeneous metapopulations, investigating and providing theoretical insights into the dynamics of local adaptation in the latter and examining the dynamics of load and extinction as well as the impact of joint ecological and evolutionary (eco-evolutionary) dynamics in the former. The thesis is divided into 5 chapters.

Chapter 1 provides a general introduction into the subject matter, clarifying concepts and ideas used throughout the thesis. In chapter 2, we explore how fast a species distributed across a heterogeneous landscape adapts to changing conditions marked by alterations in carrying capacity, selection pressure, and migration rate.

In chapter 3, we investigate how migration selection and drift influences adaptation and the maintenance of variation in a metapopulation with three habitats, an extension of previous models of adaptation in two habitats. We further develop analytical approximations for the critical threshold required for polymorphism to persist.

The focus of chapter 4 of the thesis is on understanding the interplay between ecology and evolution as coupled processes. We investigate how eco-evolutionary feedback between migration, selection, drift, and demography influences eco-evolutionary outcomes in marginal populations subject to deleterious mutation accumulation. Using simulations as well as theoretical approximations of the coupled dynamics of population size and allele frequency, we analyze how gene flow from a large mainland source influences genetic load and population size on an island (i.e., in a marginal population) under genetically realistic assumptions. Analyses of this sort are important because small isolated populations, are repeatedly affected by complex interactions between ecological and evolutionary processes, which can lead to their death. Understanding these interactions can therefore provide an insight into the conditions under which extinction risk can be mitigated in peripheral populations thus, contributing to conservation and restoration efforts.

Chapter 5 extends the analysis in chapter 4 to consider the dynamics of load (due to deleterious mutation accumulation) and extinction risk in a metapopulation. We explore the role of gene flow, selection, and dominance on load and extinction risk and further pinpoint critical thresholds required for metapopulation persistence.

Overall this research contributes to our understanding of ecological and evolutionary mechanisms that shape species’ persistence in fragmented landscapes, a crucial foundation for successful conservation efforts and biodiversity management.},
  author       = {Olusanya, Oluwafunmilola O},
  issn         = {2663 - 337X},
  pages        = {183},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Local adaptation, genetic load and extinction in metapopulations}},
  doi          = {10.15479/at:ista:14711},
  year         = {2024},
}

@phdthesis{13175,
  abstract     = {About a 100 years ago, we discovered that our universe is inherently noisy, that is, measuring any physical quantity with a precision beyond a certain point is not possible because of an omnipresent inherent noise. We call this - the quantum noise. Certain physical processes allow this quantum noise to get correlated in conjugate physical variables. These quantum correlations can be used to go beyond the potential of our inherently noisy universe and obtain a quantum advantage over the classical applications. 

Quantum noise being inherent also means that, at the fundamental level, the physical quantities are not well defined and therefore, objects can stay in multiple states at the same time. For example, the position of a particle not being well defined means that the particle is in multiple positions at the same time. About 4 decades ago, we started exploring the possibility of using objects which can be in multiple states at the same time to increase the dimensionality in computation. Thus, the field of quantum computing was born. We discovered that using quantum entanglement, a property closely related to quantum correlations, can be used to speed up computation of certain problems, such as factorisation of large numbers, faster than any known classical algorithm. Thus began the pursuit to make quantum computers a reality. 

Till date, we have explored quantum control over many physical systems including photons, spins, atoms, ions and even simple circuits made up of superconducting material. However, there persists one ubiquitous theme. The more readily a system interacts with an external field or matter, the more easily we can control it. But this also means that such a system can easily interact with a noisy environment and quickly lose its coherence. Consequently, such systems like electron spins need to be protected from the environment to ensure the longevity of their coherence. Other systems like nuclear spins are naturally protected as they do not interact easily with the environment. But, due to the same reason, it is harder to interact with such systems. 

After decades of experimentation with various systems, we are convinced that no one type of quantum system would be the best for all the quantum applications. We would need hybrid systems which are all interconnected - much like the current internet where all sorts of devices can all talk to each other - but now for quantum devices. A quantum internet. 

Optical photons are the best contenders to carry information for the quantum internet. They can carry quantum information cheaply and without much loss - the same reasons which has made them the backbone of our current internet. Following this direction, many systems, like trapped ions, have already demonstrated successful quantum links over a large distances using optical photons. However, some of the most promising contenders for quantum computing which are based on microwave frequencies have been left behind. This is because high energy optical photons can adversely affect fragile low-energy microwave systems. 

In this thesis, we present substantial progress on this missing quantum link between microwave and optics using electrooptical nonlinearities in lithium niobate. The nonlinearities are enhanced by using resonant cavities for all the involved modes leading to observation of strong direct coupling between optical and microwave frequencies. With this strong coupling we are not only able to achieve almost 100\% internal conversion efficiency with low added noise, thus presenting a quantum-enabled transducer, but also we are able to observe novel effects such as cooling of a microwave mode using optics. The strong coupling regime also leads to direct observation of dynamical backaction effect between microwave and optical frequencies which are studied in detail here. Finally, we also report first observation of microwave-optics entanglement in form of two-mode squeezed vacuum squeezed 0.7dB below vacuum level. 
With this new bridge between microwave and optics, the microwave-based quantum technologies can finally be a part of a quantum network which is based on optical photons - putting us one step closer to a future with quantum internet. },
  author       = {Sahu, Rishabh},
  isbn         = {978-3-99078-030-5},
  issn         = {2663 - 337X},
  keywords     = {quantum optics, electrooptics, quantum networks, quantum communication, transduction},
  pages        = {202},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Cavity quantum electrooptics}},
  doi          = {10.15479/at:ista:13175},
  year         = {2023},
}

@phdthesis{12900,
  abstract     = {About a 100 years ago, we discovered that our universe is inherently noisy, that is, measuring any physical quantity with a precision beyond a certain point is not possible because of an omnipresent inherent noise. We call this - the quantum noise. Certain physical processes allow this quantum noise to get correlated in conjugate physical variables. These quantum correlations can be used to go beyond the potential of our inherently noisy universe and obtain a quantum advantage over the classical applications. 

Quantum noise being inherent also means that, at the fundamental level, the physical quantities are not well defined and therefore, objects can stay in multiple states at the same time. For example, the position of a particle not being well defined means that the particle is in multiple positions at the same time. About 4 decades ago, we started exploring the possibility of using objects which can be in multiple states at the same time to increase the dimensionality in computation. Thus, the field of quantum computing was born. We discovered that using quantum entanglement, a property closely related to quantum correlations, can be used to speed up computation of certain problems, such as factorisation of large numbers, faster than any known classical algorithm. Thus began the pursuit to make quantum computers a reality. 

Till date, we have explored quantum control over many physical systems including photons, spins, atoms, ions and even simple circuits made up of superconducting material. However, there persists one ubiquitous theme. The more readily a system interacts with an external field or matter, the more easily we can control it. But this also means that such a system can easily interact with a noisy environment and quickly lose its coherence. Consequently, such systems like electron spins need to be protected from the environment to ensure the longevity of their coherence. Other systems like nuclear spins are naturally protected as they do not interact easily with the environment. But, due to the same reason, it is harder to interact with such systems. 

After decades of experimentation with various systems, we are convinced that no one type of quantum system would be the best for all the quantum applications. We would need hybrid systems which are all interconnected - much like the current internet where all sorts of devices can all talk to each other - but now for quantum devices. A quantum internet. 

Optical photons are the best contenders to carry information for the quantum internet. They can carry quantum information cheaply and without much loss - the same reasons which has made them the backbone of our current internet. Following this direction, many systems, like trapped ions, have already demonstrated successful quantum links over a large distances using optical photons. However, some of the most promising contenders for quantum computing which are based on microwave frequencies have been left behind. This is because high energy optical photons can adversely affect fragile low-energy microwave systems. 

In this thesis, we present substantial progress on this missing quantum link between microwave and optics using electrooptical nonlinearities in lithium niobate. The nonlinearities are enhanced by using resonant cavities for all the involved modes leading to observation of strong direct coupling between optical and microwave frequencies. With this strong coupling we are not only able to achieve almost 100\% internal conversion efficiency with low added noise, thus presenting a quantum-enabled transducer, but also we are able to observe novel effects such as cooling of a microwave mode using optics. The strong coupling regime also leads to direct observation of dynamical backaction effect between microwave and optical frequencies which are studied in detail here. Finally, we also report first observation of microwave-optics entanglement in form of two-mode squeezed vacuum squeezed 0.7dB below vacuum level. 
With this new bridge between microwave and optics, the microwave-based quantum technologies can finally be a part of a quantum network which is based on optical photons - putting us one step closer to a future with quantum internet. },
  author       = {Sahu, Rishabh},
  isbn         = {978-3-99078-030-5},
  issn         = {2663 - 337X},
  keywords     = {quantum optics, electrooptics, quantum networks, quantum communication, transduction},
  pages        = {190},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Cavity quantum electrooptics}},
  doi          = {10.15479/at:ista:12900},
  year         = {2023},
}

@phdthesis{11473,
  abstract     = {The polaron model is a basic model of quantum field theory describing a single particle
interacting with a bosonic field. It arises in many physical contexts. We are mostly concerned
with models applicable in the context of an impurity atom in a Bose-Einstein condensate as
well as the problem of electrons moving in polar crystals.
The model has a simple structure in which the interaction of the particle with the field is given
by a term linear in the field’s creation and annihilation operators. In this work, we investigate
the properties of this model by providing rigorous estimates on various energies relevant to the
problem. The estimates are obtained, for the most part, by suitable operator techniques which
constitute the principal mathematical substance of the thesis.
The first application of these techniques is to derive the polaron model rigorously from first
principles, i.e., from a full microscopic quantum-mechanical many-body problem involving an
impurity in an otherwise homogeneous system. We accomplish this for the N + 1 Bose gas
in the mean-field regime by showing that a suitable polaron-type Hamiltonian arises at weak
interactions as a low-energy effective theory for this problem.
In the second part, we investigate rigorously the ground state of the model at fixed momentum
and for large values of the coupling constant. Qualitatively, the system is expected to display
a transition from the quasi-particle behavior at small momenta, where the dispersion relation
is parabolic and the particle moves through the medium dragging along a cloud of phonons, to
the radiative behavior at larger momenta where the polaron decelerates and emits free phonons.
At the same time, in the strong coupling regime, the bosonic field is expected to behave purely
classically. Accordingly, the effective mass of the polaron at strong coupling is conjectured to
be asymptotically equal to the one obtained from the semiclassical counterpart of the problem,
first studied by Landau and Pekar in the 1940s. For polaron models with regularized form
factors and phonon dispersion relations of superfluid type, i.e., bounded below by a linear
function of the wavenumbers for all phonon momenta as in the interacting Bose gas, we prove
that for a large window of momenta below the radiation threshold, the energy-momentum
relation at strong coupling is indeed essentially a parabola with semi-latus rectum equal to the
Landau–Pekar effective mass, as expected.
For the Fröhlich polaron describing electrons in polar crystals where the dispersion relation is
of the optical type and the form factor is formally UV–singular due to the nature of the point
charge-dipole interaction, we are able to give the corresponding upper bound. In contrast to
the regular case, this requires the inclusion of the quantum fluctuations of the phonon field,
which makes the problem considerably more difficult.
The results are supplemented by studies on the absolute ground-state energy at strong coupling,
a proof of the divergence of the effective mass with the coupling constant for a wide class of
polaron models, as well as the discussion of the apparent UV singularity of the Fröhlich model
and the application of the techniques used for its removal for the energy estimates.
},
  author       = {Mysliwy, Krzysztof},
  issn         = {2663-337X},
  pages        = {138},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Polarons in Bose gases and polar crystals: Some rigorous energy estimates}},
  doi          = {10.15479/at:ista:11473},
  year         = {2022},
}

@phdthesis{11879,
  abstract     = {As the overall global mean surface temperature is increasing due to climate change, plant
adaptation to those stressful conditions is of utmost importance for their survival. Plants are
sessile organisms, thus to compensate for their lack of mobility, they evolved a variety of
mechanisms enabling them to flexibly adjust their physiological, growth and developmental
processes to fluctuating temperatures and to survive in harsh environments. While these unique
adaptation abilities provide an important evolutionary advantage, overall modulation of plant
growth and developmental program due to non-optimal temperature negatively affects biomass
production, crop productivity or sensitivity to pathogens. Thus, understanding molecular
processes underlying plant adaptation to increased temperature can provide important
resources for breeding strategies to ensure sufficient agricultural food production.
An increase in ambient temperature by a few degrees leads to profound changes in organ growth
including enhanced hypocotyl elongation, expansion of petioles, hyponastic growth of leaves and
cotyledons, collectively named thermomorphogenesis (Casal & Balasubramanian, 2019). Auxin,
one of the best-studied growth hormones, plays an essential role in this process by direct
activation of transcriptional and non-transcriptional processes resulting in elongation growth
(Majda & Robert, 2018).To modulate hypocotyl growth in response to high ambient temperature
(hAT), auxin needs to be redistributed accordingly. PINs, auxin efflux transporters, are key
components of the polar auxin transport (PAT) machinery, which controls the amount and
direction of auxin translocated in the plant tissues and organs(Adamowski & Friml, 2015). Hence,
PIN-mediated transport is tightly linked with thermo-morphogenesis, and interference with PAT
through either chemical or genetic means dramatically affecting the adaptive responses to hAT.
Intriguingly, despite the key role of PIN mediated transport in growth response to hAT, whether
and how PINs at the level of expression adapt to fluctuation in temperature is scarcely
understood.
With genetic, molecular and advanced bio-imaging approaches, we demonstrate the role of PIN
auxin transporters in the regulation of hypocotyl growth in response to hAT. We show that via
adjustment of PIN3, PIN4 and PIN7 expression in cotyledons and hypocotyls, auxin distribution is modulated thereby determining elongation pattern of epidermal cells at hAT. Furthermore, we
identified three Zinc-Finger (ZF) transcription factors as novel molecular components of the
thermo-regulatory network, which through negative regulation of PIN transcription adjust the
transport of auxin at hAT. Our results suggest that the ZF-PIN module might be a part of the
negative feedback loop attenuating the activity of the thermo-sensing pathway to restrain
exaggerated growth and developmental responses to hAT.},
  author       = {Artner, Christina},
  isbn         = {978-3-99078-022-0},
  issn         = {2663-337X},
  keywords     = {high ambient temperature, auxin, PINs, Zinc-Finger proteins, thermomorphogenesis, stress},
  pages        = {128},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Modulation of auxin transport via ZF proteins adjust plant response to high ambient temperature}},
  doi          = {10.15479/at:ista:11879},
  year         = {2022},
}

@article{11951,
  abstract     = {The mammalian hippocampal formation (HF) plays a key role in several higher brain functions, such as spatial coding, learning and memory. Its simple circuit architecture is often viewed as a trisynaptic loop, processing input originating from the superficial layers of the entorhinal cortex (EC) and sending it back to its deeper layers. Here, we show that excitatory neurons in layer 6b of the mouse EC project to all sub-regions comprising the HF and receive input from the CA1, thalamus and claustrum. Furthermore, their output is characterized by unique slow-decaying excitatory postsynaptic currents capable of driving plateau-like potentials in their postsynaptic targets. Optogenetic inhibition of the EC-6b pathway affects spatial coding in CA1 pyramidal neurons, while cell ablation impairs not only acquisition of new spatial memories, but also degradation of previously acquired ones. Our results provide evidence of a functional role for cortical layer 6b neurons in the adult brain.},
  author       = {Ben Simon, Yoav and Käfer, Karola and Velicky, Philipp and Csicsvari, Jozsef L and Danzl, Johann G and Jonas, Peter M},
  issn         = {2041-1723},
  journal      = {Nature Communications},
  keywords     = {General Physics and Astronomy, General Biochemistry, Genetics and Molecular Biology, General Chemistry, Multidisciplinary},
  publisher    = {Springer Nature},
  title        = {{A direct excitatory projection from entorhinal layer 6b neurons to the hippocampus contributes to spatial coding and memory}},
  doi          = {10.1038/s41467-022-32559-8},
  volume       = {13},
  year         = {2022},
}

@phdthesis{12358,
  abstract     = {The complex yarn structure of knitted and woven fabrics gives rise to both a mechanical and
visual complexity. The small-scale interactions of yarns colliding with and pulling on each
other result in drastically different large-scale stretching and bending behavior, introducing
anisotropy, curling, and more. While simulating cloth as individual yarns can reproduce this
complexity and match the quality of real fabric, it may be too computationally expensive for
large fabrics. On the other hand, continuum-based approaches do not need to discretize the
cloth at a stitch-level, but it is non-trivial to find a material model that would replicate the
large-scale behavior of yarn fabrics, and they discard the intricate visual detail. In this thesis,
we discuss three methods to try and bridge the gap between small-scale and large-scale yarn
mechanics using numerical homogenization: fitting a continuum model to periodic yarn simulations, adding mechanics-aware yarn detail onto thin-shell simulations, and quantitatively
fitting yarn parameters to physical measurements of real fabric.
To start, we present a method for animating yarn-level cloth effects using a thin-shell solver.
We first use a large number of periodic yarn-level simulations to build a model of the potential
energy density of the cloth, and then use it to compute forces in a thin-shell simulator. The
resulting simulations faithfully reproduce expected effects like the stiffening of woven fabrics
and the highly deformable nature and anisotropy of knitted fabrics at a fraction of the cost of
full yarn-level simulation.
While our thin-shell simulations are able to capture large-scale yarn mechanics, they lack
the rich visual detail of yarn-level simulations. Therefore, we propose a method to animate
yarn-level cloth geometry on top of an underlying deforming mesh in a mechanics-aware
fashion in real time. Using triangle strains to interpolate precomputed yarn geometry, we are
able to reproduce effects such as knit loops tightening under stretching at negligible cost.
Finally, we introduce a methodology for inverse-modeling of yarn-level mechanics of cloth,
based on the mechanical response of fabrics in the real world. We compile a database from
physical tests of several knitted fabrics used in the textile industry spanning diverse physical
properties like stiffness, nonlinearity, and anisotropy. We then develop a system for approximating these mechanical responses with yarn-level cloth simulation, using homogenized
shell models to speed up computation and adding some small-but-necessary extensions to
yarn-level models used in computer graphics.
},
  author       = {Sperl, Georg},
  isbn         = {978-3-99078-020-6},
  issn         = {2663-337X},
  pages        = {138},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Homogenizing yarn simulations: Large-scale mechanics, small-scale detail, and quantitative fitting}},
  doi          = {10.15479/at:ista:12103},
  year         = {2022},
}

@article{10816,
  abstract     = {Pattern separation is a fundamental brain computation that converts small differences in input patterns into large differences in output patterns. Several synaptic mechanisms of pattern separation have been proposed, including code expansion, inhibition and plasticity; however, which of these mechanisms play a role in the entorhinal cortex (EC)–dentate gyrus (DG)–CA3 circuit, a classical pattern separation circuit, remains unclear. Here we show that a biologically realistic, full-scale EC–DG–CA3 circuit model, including granule cells (GCs) and parvalbumin-positive inhibitory interneurons (PV+-INs) in the DG, is an efficient pattern separator. Both external gamma-modulated inhibition and internal lateral inhibition mediated by PV+-INs substantially contributed to pattern separation. Both local connectivity and fast signaling at GC–PV+-IN synapses were important for maximum effectiveness. Similarly, mossy fiber synapses with conditional detonator properties contributed to pattern separation. By contrast, perforant path synapses with Hebbian synaptic plasticity and direct EC–CA3 connection shifted the network towards pattern completion. Our results demonstrate that the specific properties of cells and synapses optimize higher-order computations in biological networks and might be useful to improve the deep learning capabilities of technical networks.},
  author       = {Guzmán, José and Schlögl, Alois and Espinoza Martinez, Claudia  and Zhang, Xiaomin and Suter, Benjamin and Jonas, Peter M},
  issn         = {2662-8457},
  journal      = {Nature Computational Science},
  keywords     = {general medicine},
  number       = {12},
  pages        = {830--842},
  publisher    = {Springer Nature},
  title        = {{How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network}},
  doi          = {10.1038/s43588-021-00157-1},
  volume       = {1},
  year         = {2021},
}

@article{9329,
  abstract     = {Background: To understand information coding in single neurons, it is necessary to analyze subthreshold synaptic events, action potentials (APs), and their interrelation in different behavioral states. However, detecting excitatory postsynaptic potentials (EPSPs) or currents (EPSCs) in behaving animals remains challenging, because of unfavorable signal-to-noise ratio, high frequency, fluctuating amplitude, and variable time course of synaptic events.
New method: We developed a method for synaptic event detection, termed MOD (Machine-learning Optimal-filtering Detection-procedure), which combines concepts of supervised machine learning and optimal Wiener filtering. Experts were asked to manually score short epochs of data. The algorithm was trained to obtain the optimal filter coefficients of a Wiener filter and the optimal detection threshold. Scored and unscored data were then processed with the optimal filter, and events were detected as peaks above threshold.
Results: We challenged MOD with EPSP traces in vivo in mice during spatial navigation and EPSC traces in vitro in slices under conditions of enhanced transmitter release. The area under the curve (AUC) of the receiver operating characteristics (ROC) curve was, on average, 0.894 for in vivo and 0.969 for in vitro data sets, indicating high detection accuracy and efficiency.
Comparison with existing methods: When benchmarked using a (1 − AUC)−1 metric, MOD outperformed previous methods (template-fit, deconvolution, and Bayesian methods) by an average factor of 3.13 for in vivo data sets, but showed comparable (template-fit, deconvolution) or higher (Bayesian) computational efficacy.
Conclusions: MOD may become an important new tool for large-scale, real-time analysis of synaptic activity.},
  author       = {Zhang, Xiaomin and Schlögl, Alois and Vandael, David H and Jonas, Peter M},
  issn         = {1872-678X},
  journal      = {Journal of Neuroscience Methods},
  number       = {6},
  publisher    = {Elsevier},
  title        = {{MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo}},
  doi          = {10.1016/j.jneumeth.2021.109125},
  volume       = {357},
  year         = {2021},
}

@phdthesis{10199,
  abstract     = {The design and verification of concurrent systems remains an open challenge due to the non-determinism that arises from the inter-process communication. In particular, concurrent programs are notoriously difficult both to be written correctly and to be analyzed formally, as complex thread interaction has to be accounted for. The difficulties are further exacerbated when concurrent programs get executed on modern-day hardware, which contains various buffering and caching mechanisms for efficiency reasons. This causes further subtle non-determinism, which can often produce very unintuitive behavior of the concurrent programs. Model checking is at the forefront of tackling the verification problem, where the task is to decide, given as input a concurrent system and a desired property, whether the system satisfies the property. The inherent state-space explosion problem in model checking of concurrent systems causes naïve explicit methods not to scale, thus more inventive methods are required. One such method is stateless model checking (SMC), which explores in memory-efficient manner the program executions rather than the states of the program. State-of-the-art SMC is typically coupled with partial order reduction (POR) techniques, which argue that certain executions provably produce identical system behavior, thus limiting the amount of executions one needs to explore in order to cover all possible behaviors. Another method to tackle the state-space explosion is symbolic model checking, where the considered techniques operate on a succinct implicit representation of the input system rather than explicitly accessing the system. In this thesis we present new techniques for verification of concurrent systems. We present several novel POR methods for SMC of concurrent programs under various models of semantics, some of which account for write-buffering mechanisms. Additionally, we present novel algorithms for symbolic model checking of finite-state concurrent systems, where the desired property of the systems is to ensure a formally defined notion of fairness.},
  author       = {Toman, Viktor},
  issn         = {2663-337X},
  keywords     = {concurrency, verification, model checking},
  pages        = {166},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Improved verification techniques for concurrent systems}},
  doi          = {10.15479/at:ista:10199},
  year         = {2021},
}

@article{9778,
  abstract     = {The hippocampal mossy fiber synapse is a key synapse of the trisynaptic circuit. Post-tetanic potentiation (PTP) is the most powerful form of plasticity at this synaptic connection. It is widely believed that mossy fiber PTP is an entirely presynaptic phenomenon, implying that PTP induction is input-specific, and requires neither activity of multiple inputs nor stimulation of postsynaptic neurons. To directly test cooperativity and associativity, we made paired recordings between single mossy fiber terminals and postsynaptic CA3 pyramidal neurons in rat brain slices. By stimulating non-overlapping mossy fiber inputs converging onto single CA3 neurons, we confirm that PTP is input-specific and non-cooperative. Unexpectedly, mossy fiber PTP exhibits anti-associative induction properties. EPSCs show only minimal PTP after combined pre- and postsynaptic high-frequency stimulation with intact postsynaptic Ca2+ signaling, but marked PTP in the absence of postsynaptic spiking and after suppression of postsynaptic Ca2+ signaling (10 mM EGTA). PTP is largely recovered by inhibitors of voltage-gated R- and L-type Ca2+ channels, group II mGluRs, and vacuolar-type H+-ATPase, suggesting the involvement of retrograde vesicular glutamate signaling. Transsynaptic regulation of PTP extends the repertoire of synaptic computations, implementing a brake on mossy fiber detonation and a “smart teacher” function of hippocampal mossy fiber synapses.},
  author       = {Vandael, David H and Okamoto, Yuji and Jonas, Peter M},
  issn         = {2041-1723},
  journal      = {Nature Communications},
  keywords     = {general physics and astronomy, general biochemistry, genetics and molecular biology, general chemistry},
  number       = {1},
  publisher    = {Springer},
  title        = {{Transsynaptic modulation of presynaptic short-term plasticity in hippocampal mossy fiber synapses}},
  doi          = {10.1038/s41467-021-23153-5},
  volume       = {12},
  year         = {2021},
}

@article{8001,
  abstract     = {Post-tetanic potentiation (PTP) is an attractive candidate mechanism for hippocampus-dependent short-term memory. Although PTP has a uniquely large magnitude at hippocampal mossy fiber-CA3 pyramidal neuron synapses, it is unclear whether it can be induced by natural activity and whether its lifetime is sufficient to support short-term memory. We combined in vivo recordings from granule cells (GCs), in vitro paired recordings from mossy fiber terminals and postsynaptic CA3 neurons, and “flash and freeze” electron microscopy. PTP was induced at single synapses and showed a low induction threshold adapted to sparse GC activity in vivo. PTP was mainly generated by enlargement of the readily releasable pool of synaptic vesicles, allowing multiplicative interaction with other plasticity forms. PTP was associated with an increase in the docked vesicle pool, suggesting formation of structural “pool engrams.” Absence of presynaptic activity extended the lifetime of the potentiation, enabling prolonged information storage in the hippocampal network.},
  author       = {Vandael, David H and Borges Merjane, Carolina and Zhang, Xiaomin and Jonas, Peter M},
  issn         = {10974199},
  journal      = {Neuron},
  number       = {3},
  pages        = {509--521},
  publisher    = {Elsevier},
  title        = {{Short-term plasticity at hippocampal mossy fiber synapses is induced by natural activity patterns and associated with vesicle pool engram formation}},
  doi          = {10.1016/j.neuron.2020.05.013},
  volume       = {107},
  year         = {2020},
}

@phdthesis{8386,
  abstract     = {Form versus function is a long-standing debate in various design-related fields, such as architecture as well as graphic and industrial design. A good design that balances form and function often requires considerable human effort and collaboration among experts from different professional fields. Computational design tools provide a new paradigm for designing functional objects. In computational design, form and function are represented as mathematical
quantities, with the help of numerical and combinatorial algorithms, they can assist even novice users in designing versatile models that exhibit their desired functionality. This thesis presents three disparate research studies on the computational design of functional objects: The appearance of 3d print—we optimize the volumetric material distribution for faithfully replicating colored surface texture in 3d printing; the dynamic motion of mechanical structures—
our design system helps the novice user to retarget various mechanical templates with different functionality to complex 3d shapes; and a more abstract functionality, multistability—our algorithm automatically generates models that exhibit multiple stable target poses. For each of these cases, our computational design tools not only ensure the functionality of the results but also permit the user aesthetic freedom over the form. Moreover, fabrication constraints
were taken into account, which allow for the immediate creation of physical realization via 3D printing or laser cutting.},
  author       = {Zhang, Ran},
  issn         = {2663-337X},
  pages        = {148},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Structure-aware computational design and its application to 3D printable volume scattering, mechanism, and multistability}},
  doi          = {10.15479/AT:ISTA:8386},
  year         = {2020},
}

@unpublished{9750,
  abstract     = {Tension of the actomyosin cell cortex plays a key role in determining cell-cell contact growth and size. The level of cortical tension outside of the cell-cell contact, when pulling at the contact edge, scales with the total size to which a cell-cell contact can grow1,2. Here we show in zebrafish primary germ layer progenitor cells that this monotonic relationship only applies to a narrow range of cortical tension increase, and that above a critical threshold, contact size inversely scales with cortical tension. This switch from cortical tension increasing to decreasing progenitor cell-cell contact size is caused by cortical tension promoting E-cadherin anchoring to the actomyosin cytoskeleton, thereby increasing clustering and stability of E-cadherin at the contact. Once tension-mediated E-cadherin stabilization at the contact exceeds a critical threshold level, the rate by which the contact expands in response to pulling forces from the cortex sharply drops, leading to smaller contacts at physiologically relevant timescales of contact formation. Thus, the activity of cortical tension in expanding cell-cell contact size is limited by tension stabilizing E-cadherin-actin complexes at the contact.},
  author       = {Slovakova, Jana and Sikora, Mateusz K and Caballero Mancebo, Silvia and Krens, Gabriel and Kaufmann, Walter and Huljev, Karla and Heisenberg, Carl-Philipp J},
  booktitle    = {bioRxiv},
  pages        = {41},
  publisher    = {Cold Spring Harbor Laboratory},
  title        = {{Tension-dependent stabilization of E-cadherin limits cell-cell contact expansion}},
  doi          = {10.1101/2020.11.20.391284},
  year         = {2020},
}

@phdthesis{7186,
  abstract     = {Tissue morphogenesis in developmental or physiological processes is regulated by molecular
and mechanical signals. While the molecular signaling cascades are increasingly well
described, the mechanical signals affecting tissue shape changes have only recently been
studied in greater detail. To gain more insight into the mechanochemical and biophysical
basis of an epithelial spreading process (epiboly) in early zebrafish development, we studied
cell-cell junction formation and actomyosin network dynamics at the boundary between
surface layer epithelial cells (EVL) and the yolk syncytial layer (YSL). During zebrafish epiboly,
the cell mass sitting on top of the yolk cell spreads to engulf the yolk cell by the end of
gastrulation. It has been previously shown that an actomyosin ring residing within the YSL
pulls on the EVL tissue through a cable-constriction and a flow-friction motor, thereby
dragging the tissue vegetal wards. Pulling forces are likely transmitted from the YSL
actomyosin ring to EVL cells; however, the nature and formation of the junctional structure
mediating this process has not been well described so far. Therefore, our main aim was to
determine the nature, dynamics and potential function of the EVL-YSL junction during this
epithelial tissue spreading. Specifically, we show that the EVL-YSL junction is a
mechanosensitive structure, predominantly made of tight junction (TJ) proteins. The process
of TJ mechanosensation depends on the retrograde flow of non-junctional, phase-separated
Zonula Occludens-1 (ZO-1) protein clusters towards the EVL-YSL boundary. Interestingly, we
could demonstrate that ZO-1 is present in a non-junctional pool on the surface of the yolk
cell, and ZO-1 undergoes a phase separation process that likely renders the protein
responsive to flows. These flows are directed towards the junction and mediate proper
tension-dependent recruitment of ZO-1. Upon reaching the EVL-YSL junction ZO-1 gets
incorporated into the junctional pool mediated through its direct actin-binding domain.
When the non-junctional pool and/or ZO-1 direct actin binding is absent, TJs fail in their
proper mechanosensitive responses resulting in slower tissue spreading. We could further
demonstrate that depletion of ZO proteins within the YSL results in diminished actomyosin
ring formation. This suggests that a mechanochemical feedback loop is at work during
zebrafish epiboly: ZO proteins help in proper actomyosin ring formation and actomyosin
contractility and flows positively influence ZO-1 junctional recruitment. Finally, such a
mesoscale polarization process mediated through the flow of phase-separated protein
clusters might have implications for other processes such as immunological synapse
formation, C. elegans zygote polarization and wound healing.},
  author       = {Schwayer, Cornelia},
  issn         = {2663-337X},
  pages        = {107},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Mechanosensation of tight junctions depends on ZO-1 phase separation and flow}},
  doi          = {10.15479/AT:ISTA:7186},
  year         = {2019},
}

@article{6328,
  abstract     = {During metazoan development, immune surveillance and cancer dissemination, cells migrate in complex three-dimensional microenvironments1,2,3. These spaces are crowded by cells and extracellular matrix, generating mazes with differently sized gaps that are typically smaller than the diameter of the migrating cell4,5. Most mesenchymal and epithelial cells and some—but not all—cancer cells actively generate their migratory path using pericellular tissue proteolysis6. By contrast, amoeboid cells such as leukocytes use non-destructive strategies of locomotion7, raising the question how these extremely fast cells navigate through dense tissues. Here we reveal that leukocytes sample their immediate vicinity for large pore sizes, and are thereby able to choose the path of least resistance. This allows them to circumnavigate local obstacles while effectively following global directional cues such as chemotactic gradients. Pore-size discrimination is facilitated by frontward positioning of the nucleus, which enables the cells to use their bulkiest compartment as a mechanical gauge. Once the nucleus and the closely associated microtubule organizing centre pass the largest pore, cytoplasmic protrusions still lingering in smaller pores are retracted. These retractions are coordinated by dynamic microtubules; when microtubules are disrupted, migrating cells lose coherence and frequently fragment into migratory cytoplasmic pieces. As nuclear positioning in front of the microtubule organizing centre is a typical feature of amoeboid migration, our findings link the fundamental organization of cellular polarity to the strategy of locomotion.},
  author       = {Renkawitz, Jörg and Kopf, Aglaja and Stopp, Julian A and de Vries, Ingrid and Driscoll, Meghan K. and Merrin, Jack and Hauschild, Robert and Welf, Erik S. and Danuser, Gaudenz and Fiolka, Reto and Sixt, Michael K},
  journal      = {Nature},
  pages        = {546--550},
  publisher    = {Springer Nature},
  title        = {{Nuclear positioning facilitates amoeboid migration along the path of least resistance}},
  doi          = {10.1038/s41586-019-1087-5},
  volume       = {568},
  year         = {2019},
}

@article{308,
  abstract     = {Migrating cells penetrate tissue barriers during development, inflammatory responses, and tumor metastasis. We study if migration in vivo in such three-dimensionally confined environments requires changes in the mechanical properties of the surrounding cells using embryonic Drosophila melanogaster hemocytes, also called macrophages, as a model. We find that macrophage invasion into the germband through transient separation of the apposing ectoderm and mesoderm requires cell deformations and reductions in apical tension in the ectoderm. Interestingly, the genetic pathway governing these mechanical shifts acts downstream of the only known tumor necrosis factor superfamily member in Drosophila, Eiger, and its receptor, Grindelwald. Eiger-Grindelwald signaling reduces levels of active Myosin in the germband ectodermal cortex through the localization of a Crumbs complex component, Patj (Pals-1-associated tight junction protein). We therefore elucidate a distinct molecular pathway that controls tissue tension and demonstrate the importance of such regulation for invasive migration in vivo.},
  author       = {Ratheesh, Aparna and Biebl, Julia and Smutny, Michael and Veselá, Jana and Papusheva, Ekaterina and Krens, Gabriel and Kaufmann, Walter and György, Attila and Casano, Alessandra M and Siekhaus, Daria E},
  journal      = {Developmental Cell},
  number       = {3},
  pages        = {331 -- 346},
  publisher    = {Elsevier},
  title        = {{Drosophila TNF modulates tissue tension in the embryo to facilitate macrophage invasive migration}},
  doi          = {10.1016/j.devcel.2018.04.002},
  volume       = {45},
  year         = {2018},
}

@article{328,
  abstract     = {The drag of turbulent flows can be drastically decreased by adding small amounts of high molecular weight polymers. While drag reduction initially increases with polymer concentration, it eventually saturates to what is known as the maximum drag reduction (MDR) asymptote; this asymptote is generally attributed to the dynamics being reduced to a marginal yet persistent state of subdued turbulent motion. Contrary to this accepted view, we show that, for an appropriate choice of parameters, polymers can reduce the drag beyond the suggested asymptotic limit, eliminating turbulence and giving way to laminar flow. At higher polymer concentrations, however, the laminar state becomes unstable, resulting in a fluctuating flow with the characteristic drag of the MDR asymptote. Our findings indicate that the asymptotic state is hence dynamically disconnected from ordinary turbulence. © 2018 American Physical Society.},
  author       = {Choueiri, George H and Lopez Alonso, Jose M and Hof, Björn},
  journal      = {Physical Review Letters},
  number       = {12},
  publisher    = {American Physical Society},
  title        = {{Exceeding the asymptotic limit of polymer drag reduction}},
  doi          = {10.1103/PhysRevLett.120.124501},
  volume       = {120},
  year         = {2018},
}

@article{15,
  abstract     = {Although much is known about the physiological framework of T cell motility, and numerous rate-limiting molecules have been identified through loss-of-function approaches, an integrated functional concept of T cell motility is lacking. Here, we used in vivo precision morphometry together with analysis of cytoskeletal dynamics in vitro to deconstruct the basic mechanisms of T cell migration within lymphatic organs. We show that the contributions of the integrin LFA-1 and the chemokine receptor CCR7 are complementary rather than positioned in a linear pathway, as they are during leukocyte extravasation from the blood vasculature. Our data demonstrate that CCR7 controls cortical actin flows, whereas integrins mediate substrate friction that is sufficient to drive locomotion in the absence of considerable surface adhesions and plasma membrane flux.},
  author       = {Hons, Miroslav and Kopf, Aglaja and Hauschild, Robert and Leithner, Alexander F and Gärtner, Florian R and Abe, Jun and Renkawitz, Jörg and Stein, Jens and Sixt, Michael K},
  journal      = {Nature Immunology},
  number       = {6},
  pages        = {606 -- 616},
  publisher    = {Nature Publishing Group},
  title        = {{Chemokines and integrins independently tune actin flow and substrate friction during intranodal migration of T cells}},
  doi          = {10.1038/s41590-018-0109-z},
  volume       = {19},
  year         = {2018},
}

@article{437,
  abstract     = {Dendritic cells (DCs) are sentinels of the adaptive immune system that reside in peripheral organs of mammals. Upon pathogen encounter, they undergo maturation and up-regulate the chemokine receptor CCR7 that guides them along gradients of its chemokine ligands CCL19 and 21 to the next draining lymph node. There, DCs present peripherally acquired antigen to naïve T cells, thereby triggering adaptive immunity.},
  author       = {Leithner, Alexander F and Renkawitz, Jörg and De Vries, Ingrid and Hauschild, Robert and Haecker, Hans and Sixt, Michael K},
  journal      = {European Journal of Immunology},
  number       = {6},
  pages        = {1074 -- 1077},
  publisher    = {Wiley-Blackwell},
  title        = {{Fast and efficient genetic engineering of hematopoietic precursor cells for the study of dendritic cell migration}},
  doi          = {10.1002/eji.201747358},
  volume       = {48},
  year         = {2018},
}

