@phdthesis{14506,
  abstract     = {Payment channel networks are a promising approach to improve the scalability bottleneck
of cryptocurrencies. Two design principles behind payment channel networks are
efficiency and privacy. Payment channel networks improve efficiency by allowing users
to transact in a peer-to-peer fashion along multi-hop routes in the network, avoiding
the lengthy process of consensus on the blockchain. Transacting over payment channel
networks also improves privacy as these transactions are not broadcast to the blockchain.
Despite the influx of recent protocols built on top of payment channel networks and
their analysis, a common shortcoming of many of these protocols is that they typically
focus only on either improving efficiency or privacy, but not both. Another limitation
on the efficiency front is that the models used to model actions, costs and utilities of
users are limited or come with unrealistic assumptions.
This thesis aims to address some of the shortcomings of recent protocols and algorithms
on payment channel networks, particularly in their privacy and efficiency aspects. We
first present a payment route discovery protocol based on hub labelling and private
information retrieval that hides the route query and is also efficient. We then present
a rebalancing protocol that formulates the rebalancing problem as a linear program
and solves the linear program using multiparty computation so as to hide the channel
balances. The rebalancing solution as output by our protocol is also globally optimal.
We go on to develop more realistic models of the action space, costs, and utilities of
both existing and new users that want to join the network. In each of these settings,
we also develop algorithms to optimise the utility of these users with good guarantees
on the approximation and competitive ratios.},
  author       = {Yeo, Michelle X},
  issn         = {2663-337X},
  pages        = {162},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Advances in efficiency and privacy in payment channel network analysis}},
  doi          = {10.15479/14506},
  year         = {2023},
}

@inproceedings{14490,
  abstract     = {Payment channel networks (PCNs) are a promising solution to the scalability problem of cryptocurrencies. Any two users connected by a payment channel in the network can theoretically send an unbounded number of instant, costless transactions between them. Users who are not directly connected can also transact with each other in a multi-hop fashion. In this work, we study the incentive structure behind the creation of payment channel networks, particularly from the point of view of a single user that wants to join the network. We define a utility function for a new user in terms of expected revenue, expected fees, and the cost of creating channels, and then provide constant factor approximation algorithms that optimise the utility function given a certain budget. Additionally, we take a step back from a single user to the whole network and examine the parameter spaces under which simple graph topologies form a Nash equilibrium.},
  author       = {Avarikioti, Zeta and Lizurej, Tomasz and Michalak, Tomasz and Yeo, Michelle X},
  booktitle    = {43rd International Conference on Distributed Computing Systems},
  isbn         = {9798350339864},
  issn         = {2575-8411},
  location     = {Hong Kong, China},
  pages        = {603--613},
  publisher    = {IEEE},
  title        = {{Lightning creation games}},
  doi          = {10.1109/ICDCS57875.2023.00037},
  volume       = {2023},
  year         = {2023},
}

@article{13128,
  abstract     = {Given 𝐴 ⊆𝐺⁡𝐿2⁡(𝔽𝑞), we prove that there exist disjoint subsets 𝐵,𝐶 ⊆𝐴 such that 𝐴 =𝐵 ⊔𝐶 and their additive and multiplicative energies satisfying
max⁡{𝐸+⁡(𝐵),𝐸×⁡(𝐶)}≪|𝐴|3/𝑀⁡(|𝐴|), where
𝑀⁡(|𝐴|)=min⁡{𝑞4/3/|𝐴|1/3⁢(log⁡|𝐴|)2/3, |𝐴|4/5/𝑞13/5⁢(log⁡|𝐴|)27/10}.
 
We also study some related questions on moderate expanders over matrix rings, namely, for 𝐴,𝐵,𝐶 ⊆𝐺⁡𝐿2⁡(𝔽𝑞), we have
|𝐴⁢𝐵+𝐶|, |(𝐴+𝐵)⁢𝐶|≫𝑞4,
 whenever |𝐴|⁢|𝐵|⁢|𝐶| ≫𝑞10+1/2. These improve earlier results due to Karabulut, Koh, Pham, Shen, and Vinh ([2019], Expanding phenomena over matrix rings, 𝐹⁡𝑜⁢𝑟⁢𝑢⁢𝑚⁢𝑀⁢𝑎⁢𝑡⁢ℎ., 31, 951–970).},
  author       = {Mohammadi, Ali and Pham, Thang and Wang, Yiting},
  issn         = {1496-4287},
  journal      = {Canadian Mathematical Bulletin},
  number       = {4},
  pages        = {1280--1295},
  publisher    = {Cambridge University Press},
  title        = {{An energy decomposition theorem for matrices and related questions}},
  doi          = {10.4153/S000843952300036X},
  volume       = {66},
  year         = {2023},
}

@article{12679,
  abstract     = {How to generate a brain of correct size and with appropriate cell-type diversity during development is a major question in Neuroscience. In the developing neocortex, radial glial progenitor (RGP) cells are the main neural stem cells that produce cortical excitatory projection neurons, glial cells, and establish the prospective postnatal stem cell niche in the lateral ventricles. RGPs follow a tightly orchestrated developmental program that when disrupted can result in severe cortical malformations such as microcephaly and megalencephaly. The precise cellular and molecular mechanisms instructing faithful RGP lineage progression are however not well understood. This review will summarize recent conceptual advances that contribute to our understanding of the general principles of RGP lineage progression.},
  author       = {Hippenmeyer, Simon},
  issn         = {0959-4388},
  journal      = {Current Opinion in Neurobiology},
  keywords     = {General Neuroscience},
  number       = {4},
  publisher    = {Elsevier},
  title        = {{Principles of neural stem cell lineage progression: Insights from developing cerebral cortex}},
  doi          = {10.1016/j.conb.2023.102695},
  volume       = {79},
  year         = {2023},
}

@misc{13126,
  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       = {Danzl, Johann G},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Research data for the publication "Imaging brain tissue architecture across millimeter to nanometer scales"}},
  doi          = {10.15479/AT:ISTA:13126},
  year         = {2023},
}

@article{13267,
  abstract     = {Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure–function relationships of the brain’s complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.},
  author       = {Velicky, Philipp and Miguel Villalba, Eder and Michalska, Julia M and Lyudchik, Julia and Wei, Donglai and Lin, Zudi and Watson, Jake and Troidl, Jakob and Beyer, Johanna and Ben Simon, Yoav and Sommer, Christoph M and Jahr, Wiebke and Cenameri, Alban and Broichhagen, Johannes and Grant, Seth G.N. and Jonas, Peter M and Novarino, Gaia and Pfister, Hanspeter and Bickel, Bernd and Danzl, Johann G},
  issn         = {1548-7105},
  journal      = {Nature Methods},
  pages        = {1256--1265},
  publisher    = {Springer Nature},
  title        = {{Dense 4D nanoscale reconstruction of living brain tissue}},
  doi          = {10.1038/s41592-023-01936-6},
  volume       = {20},
  year         = {2023},
}

@misc{12817,
  abstract     = {3D-reconstruction of living brain tissue down to individual synapse level would create opportunities for decoding the dynamics and structure-function relationships of the brain’s complex and dense information processing network. However, it has been hindered by insufficient 3D-resolution, inadequate signal-to-noise-ratio, and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine learning technology, LIONESS (Live Information-Optimized Nanoscopy Enabling Saturated Segmentation). It leverages optical modifications to stimulated emission depletion (STED) microscopy in comprehensively, extracellularly labelled tissue and prior information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise-ratio, and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D-reconstruction at synapse level incorporating molecular, activity, and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.},
  author       = {Danzl, Johann G},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Research data for the publication "Dense 4D nanoscale reconstruction of living brain tissue"}},
  doi          = {10.15479/AT:ISTA:12817},
  year         = {2023},
}

@article{14770,
  abstract     = {We developed LIONESS, a technology that leverages improvements to optical super-resolution microscopy and prior information on sample structure via machine learning to overcome the limitations (in 3D-resolution, signal-to-noise ratio and light exposure) of optical microscopy of living biological specimens. LIONESS enables dense reconstruction of living brain tissue and morphodynamics visualization at the nanoscale.},
  author       = {Danzl, Johann G and Velicky, Philipp},
  issn         = {1548-7105},
  journal      = {Nature Methods},
  keywords     = {Cell Biology, Molecular Biology, Biochemistry, Biotechnology},
  number       = {8},
  pages        = {1141--1142},
  publisher    = {Springer Nature},
  title        = {{LIONESS enables 4D nanoscale reconstruction of living brain tissue}},
  doi          = {10.1038/s41592-023-01937-5},
  volume       = {20},
  year         = {2023},
}

@phdthesis{13107,
  abstract     = {Within the human body, the brain exhibits the highest rate of energy consumption amongst all organs, with the majority of generated ATP being utilized to sustain neuronal activity. Therefore, the metabolism of the mature cerebral cortex is geared towards preserving metabolic homeostasis whilst generating significant amounts of energy. This requires a precise interplay between diverse metabolic pathways, spanning from a tissue-wide scale to the level of individual neurons. Disturbances to this delicate metabolic equilibrium, such as those resulting from maternal malnutrition
or mutations affecting metabolic enzymes, often result in neuropathological variants of neurodevelopment. For instance, mutations in SLC7A5, a transporter of metabolically essential large neutral amino acids (LNAAs), have been associated with autism and microcephaly. However, despite recent progress in the field, the extent of metabolic restructuring that occurs within the developing brain and the corresponding alterations in nutrient demands during various critical periods remain largely unknown. To investigate this, we performed metabolomic profiling of the murine cerebral cortex to characterize the metabolic state of the forebrain at different developmental stages. We found that the developing cortex undergoes substantial metabolic reprogramming, with specific sets of metabolites displaying stage-specific changes. According to our observations, we determined a distinct temporal period in postnatal development during which the cortex displays heightened reliance on LNAAs. Hence, using a conditional knock-out mouse model, we deleted Slc7a5 in neural cells, allowing us to monitor the impact of a perturbed neuronal metabolic state across multiple developmental stages of corticogenesis. We found that manipulating the levels of essential LNAAs in cortical neurons in vivo affects one particular perinatal developmental period critical for cortical network refinement. Abnormally low intracellular LNAA levels result in cell-autonomous alterations in neuronal lipid metabolism, excitability, and survival during this particular time window. Although most of the effects of Slc7a5 deletion on neuronal physiology are transient, derailment of these processes during this brief but crucial window leads to long-term circuit dysfunction in mice. In conclusion, out data indicate that the cerebral cortex undergoes significant metabolic reorganization during development. This process involves the intricate integration of multiple metabolic pathways to ensure optimal neuronal function throughout different developmental stages. Our findings offer a paradigm for understanding how neurons synchronize the expression of nutrient-related genes with their activity to allow proper brain maturation. Further, our results demonstrate that disruptions in these precisely calibrated metabolic processes during critical periods of brain development may result in neuropathological outcomes in mice and in humans.},
  author       = {Knaus, Lisa},
  issn         = {2663-337X},
  pages        = {147},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{The metabolism of the developing brain : How large neutral amino acids modulate perinatal neuronal excitability and survival}},
  doi          = {10.15479/at:ista:13107},
  year         = {2023},
}

@article{12802,
  abstract     = {Little is known about the critical metabolic changes that neural cells have to undergo during development and how temporary shifts in this program can influence brain circuitries and behavior. Inspired by the discovery that mutations in SLC7A5, a transporter of metabolically essential large neutral amino acids (LNAAs), lead to autism, we employed metabolomic profiling to study the metabolic states of the cerebral cortex across different developmental stages. We found that the forebrain undergoes significant metabolic remodeling throughout development, with certain groups of metabolites showing stage-specific changes, but what are the consequences of perturbing this metabolic program? By manipulating Slc7a5 expression in neural cells, we found that the metabolism of LNAAs and lipids are interconnected in the cortex. Deletion of Slc7a5 in neurons affects the postnatal metabolic state, leading to a shift in lipid metabolism. Additionally, it causes stage- and cell-type-specific alterations in neuronal activity patterns, resulting in a long-term circuit dysfunction.},
  author       = {Knaus, Lisa and Basilico, Bernadette and Malzl, Daniel and Gerykova Bujalkova, Maria and Smogavec, Mateja and Schwarz, Lena A. and Gorkiewicz, Sarah and Amberg, Nicole and Pauler, Florian and Knittl-Frank, Christian and Tassinari, Marianna and Maulide, Nuno and Rülicke, Thomas and Menche, Jörg and Hippenmeyer, Simon and Novarino, Gaia},
  issn         = {0092-8674},
  journal      = {Cell},
  keywords     = {General Biochemistry, Genetics and Molecular Biology},
  number       = {9},
  pages        = {1950--1967.e25},
  publisher    = {Elsevier},
  title        = {{Large neutral amino acid levels tune perinatal neuronal excitability and survival}},
  doi          = {10.1016/j.cell.2023.02.037},
  volume       = {186},
  year         = {2023},
}

@article{14484,
  abstract     = {Intercellular signaling molecules, known as morphogens, act at a long range in developing tissues to provide spatial information and control properties such as cell fate and tissue growth. The production, transport, and removal of morphogens shape their concentration profiles in time and space. Downstream signaling cascades and gene regulatory networks within cells then convert the spatiotemporal morphogen profiles into distinct cellular responses. Current challenges are to understand the diverse molecular and cellular mechanisms underlying morphogen gradient formation, as well as the logic of downstream regulatory circuits involved in morphogen interpretation. This knowledge, combining experimental and theoretical results, is essential to understand emerging properties of morphogen-controlled systems, such as robustness and scaling.},
  author       = {Kicheva, Anna and Briscoe, James},
  issn         = {1530-8995},
  journal      = {Annual Review of Cell and Developmental Biology},
  pages        = {91--121},
  publisher    = {Annual Reviews},
  title        = {{Control of tissue development by morphogens}},
  doi          = {10.1146/annurev-cellbio-020823-011522},
  volume       = {39},
  year         = {2023},
}

@article{14517,
  abstract     = {State-of-the-art transmon qubits rely on large capacitors, which systematically improve their coherence due to reduced surface-loss participation. However, this approach increases both the footprint and the parasitic cross-coupling and is ultimately limited by radiation losses—a potential roadblock for scaling up quantum processors to millions of qubits. In this work we present transmon qubits with sizes as low as 36 × 39 µm2 with  100-nm-wide vacuum-gap capacitors that are micromachined from commercial silicon-on-insulator wafers and shadow evaporated with aluminum. We achieve a vacuum participation ratio up to 99.6% in an in-plane design that is compatible with standard coplanar circuits. Qubit relaxationtime measurements for small gaps with high zero-point electric field variance of up to 22 V/m reveal a double exponential decay indicating comparably strong qubit interaction with long-lived two-level systems. The exceptionally high selectivity of up to 20 dB to the superconductor-vacuum interface allows us to precisely back out the sub-single-photon dielectric loss tangent of aluminum oxide previously exposed to ambient conditions. In terms of future scaling potential, we achieve a ratio of qubit quality factor to a footprint area equal to 20 µm−2, which is comparable with the highest T1 devices relying on larger geometries, a value that could improve substantially for lower surface-loss superconductors. },
  author       = {Zemlicka, Martin and Redchenko, Elena and Peruzzo, Matilda and Hassani, Farid and Trioni, Andrea and Barzanjeh, Shabir and Fink, Johannes M},
  issn         = {2331-7019},
  journal      = {Physical Review Applied},
  number       = {4},
  publisher    = {American Physical Society},
  title        = {{Compact vacuum-gap transmon qubits: Selective and sensitive probes for superconductor surface losses}},
  doi          = {10.1103/PhysRevApplied.20.044054},
  volume       = {20},
  year         = {2023},
}

@article{13106,
  abstract     = {Quantum entanglement is a key resource in currently developed quantum technologies. Sharing this fragile property between superconducting microwave circuits and optical or atomic systems would enable new functionalities, but this has been hindered by an energy scale mismatch of >104 and the resulting mutually imposed loss and noise. In this work, we created and verified entanglement between microwave and optical fields in a millikelvin environment. Using an optically pulsed superconducting electro-optical device, we show entanglement between propagating microwave and optical fields in the continuous variable domain. This achievement not only paves the way for entanglement between superconducting circuits and telecom wavelength light, but also has wide-ranging implications for hybrid quantum networks in the context of modularization, scaling, sensing, and cross-platform verification.},
  author       = {Sahu, Rishabh and Qiu, Liu and Hease, William J and Arnold, Georg M and Minoguchi, Y. and Rabl, P. and Fink, Johannes M},
  issn         = {1095-9203},
  journal      = {Science},
  keywords     = {Multidisciplinary},
  number       = {6646},
  pages        = {718--721},
  publisher    = {American Association for the Advancement of Science},
  title        = {{Entangling microwaves with light}},
  doi          = {10.1126/science.adg3812},
  volume       = {380},
  year         = {2023},
}

@misc{13122,
  abstract     = {Data for submitted article "Entangling microwaves with light" at arXiv:2301.03315v1},
  author       = {Sahu, Rishabh},
  publisher    = {Zenodo},
  title        = {{Entangling microwaves with light}},
  doi          = {10.5281/ZENODO.7789417},
  year         = {2023},
}

@article{13227,
  abstract     = {Currently available quantum processors are dominated by noise, which severely limits their applicability and motivates the search for new physical qubit encodings. In this work, we introduce the inductively shunted transmon, a weakly flux-tunable superconducting qubit that offers charge offset protection for all levels and a 20-fold reduction in flux dispersion compared to the state-of-the-art resulting in a constant coherence over a full flux quantum. The parabolic confinement provided by the inductive shunt as well as the linearity of the geometric superinductor facilitates a high-power readout that resolves quantum jumps with a fidelity and QND-ness of >90% and without the need for a Josephson parametric amplifier. Moreover, the device reveals quantum tunneling physics between the two prepared fluxon ground states with a measured average decay time of up to 3.5 h. In the future, fast time-domain control of the transition matrix elements could offer a new path forward to also achieve full qubit control in the decay-protected fluxon basis.},
  author       = {Hassani, Farid and Peruzzo, Matilda and Kapoor, Lucky and Trioni, Andrea and Zemlicka, Martin and Fink, Johannes M},
  issn         = {2041-1723},
  journal      = {Nature Communications},
  publisher    = {Springer Nature},
  title        = {{Inductively shunted transmons exhibit noise insensitive plasmon states and a fluxon decay exceeding 3 hours}},
  doi          = {10.1038/s41467-023-39656-2},
  volume       = {14},
  year         = {2023},
}

@misc{13124,
  abstract     = {This dataset comprises all data shown in the figures of the submitted article "Tunable directional photon scattering from a pair of superconducting qubits" at arXiv:2205.03293. Additional raw data are available from the corresponding author on reasonable request.},
  author       = {Redchenko, Elena and Poshakinskiy, Alexander and Sett, Riya and Zemlicka, Martin and Poddubny, Alexander and Fink, Johannes M},
  publisher    = {Zenodo},
  title        = {{Tunable directional photon scattering from a pair of superconducting qubits}},
  doi          = {10.5281/ZENODO.7858567},
  year         = {2023},
}

@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},
}

@article{13049,
  abstract     = {We propose a computational design approach for covering a surface with individually addressable RGB LEDs, effectively forming a low-resolution surface screen. To achieve a low-cost and scalable approach, we propose creating designs from flat PCB panels bent in-place along the surface of a 3D printed core. Working with standard rigid PCBs enables the use of
established PCB manufacturing services, allowing the fabrication of designs with several hundred LEDs. 
Our approach optimizes the PCB geometry for folding, and then jointly optimizes the LED packing, circuit and routing, solving a challenging layout problem under strict manufacturing requirements. Unlike paper, PCBs cannot bend beyond a certain point without breaking. Therefore, we introduce parametric cut patterns acting as hinges, designed to allow bending while remaining compact. To tackle the joint optimization of placement, circuit and routing, we propose a specialized algorithm that splits the global problem into one sub-problem per triangle, which is then individually solved.
Our technique generates PCB blueprints in a completely automated way. After being fabricated by a PCB manufacturing service, the boards are bent and glued by the user onto the 3D printed support. We demonstrate our technique on a range of physical models and virtual examples, creating intricate surface light patterns from hundreds of LEDs.},
  author       = {Freire, Marco and Bhargava, Manas and Schreck, Camille and Hugron, Pierre-Alexandre and Bickel, Bernd and Lefebvre, Sylvain},
  issn         = {1557-7368},
  journal      = {Transactions on Graphics},
  keywords     = {PCB design and layout, Mesh geometry models},
  location     = {Los Angeles, CA, United States},
  number       = {4},
  publisher    = {Association for Computing Machinery},
  title        = {{PCBend: Light up your 3D shapes with foldable circuit boards}},
  doi          = {10.1145/3592411},
  volume       = {42},
  year         = {2023},
}

@inproceedings{14771,
  abstract     = {Pruning—that is, setting a significant subset of the parameters of a neural network to zero—is one of the most popular methods of model compression. Yet, several recent works have raised the issue that pruning may induce or exacerbate bias in the output of the compressed model. Despite existing evidence for this phenomenon, the relationship between neural network pruning and induced bias is not well-understood. In this work, we systematically investigate and characterize this phenomenon in Convolutional Neural Networks for computer vision. First, we show that it is in fact possible to obtain highly-sparse models, e.g. with less than 10% remaining weights, which do not decrease in accuracy nor substantially increase in bias when compared to dense models. At the same time, we also find that, at higher sparsities, pruned models exhibit higher uncertainty in their outputs, as well as increased correlations, which we directly link to increased bias. We propose easy-to-use criteria which, based only on the uncompressed model, establish whether bias will increase with pruning, and identify the samples most susceptible to biased predictions post-compression. Our code can be found at https://github.com/IST-DASLab/pruned-vision-model-bias.},
  author       = {Iofinova, Eugenia B and Peste, Elena-Alexandra and Alistarh, Dan-Adrian},
  booktitle    = {2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  issn         = {2575-7075},
  location     = {Vancouver, BC, Canada},
  pages        = {24364--24373},
  publisher    = {IEEE},
  title        = {{Bias in pruned vision models: In-depth analysis and countermeasures}},
  doi          = {10.1109/cvpr52729.2023.02334},
  year         = {2023},
}