arXiv subjects

Sahil Patel

Publications and source records attributed to Sahil Patel.

15 recordsLinked to original sources

arXiv2025

Towards Breath Based Diagnostics via Water-mediated Capture of Synthetic Breath Biomarkers in SERS-active Plasmonic Nanogaps

Volatile organic compounds (VOCs) are valuable health indicators, with synthetic breath biomarkers offering rapid and disease specific diagnostics. However, their <100 ppb level exhalation requires mass spectrometry, limiting clinical integration. Surface-enhanced Raman spectroscopy (SERS) offers a portable, cost-effective alternative. Yet, detecting synthetic breath biomarkers, with inherently low Raman cross-sections, at <100 ppb remains challenging. We demonstrate SERS detection down to clinically relevant 10 ppb via water-mediated trapping in hydroxylated nanoporous silica-coated plasmonic nanogaps, using pentafluoropropylamine (PFP) as a representative synthetic breath biomarker. Uniform nanogaps, with >1000 times electric field enhancement, were generated between a gold film and gold-silica core-shell nanoparticle assemblies using electric field-driven evaporation. Oxygen plasma treatment hydroxylated the silica, enabling water-mediated hydrogen bonding that strengthened PFP adsorption, confirmed by density functional theory. This mechanism improved SERS sensitivity by 10000 fold, enabling ppb level PFP detection in mouse bronchial fluid and establishing a VOC capturing SERS platform for breath-based diagnostics.

physics.app-ph↗

arXiv2025

Towards High-Efficiency Particle Detection Using Superconducting Microwire Arrays

We present a detailed study of an 8-channel $1\times1$ mm$^{2}$ WSi superconducting microwire single photon detector (SMSPD) array exposed to 120 GeV hadron beam and 120 GeV muon beam at the CERN Super Proton Synchrotron H6 beamline. Following up on our first detailed characterization of the efficiency and response of an SMSPD fabricated on a 3 nm WSi film, we report measurements of enhanced particle detection efficiency using a sensor fabricated from a thicker 4.7nm-thick WSi film. We also report the first SMSPD detection efficiency measurement made for muons. Measurements are enabled by a silicon tracking telescope providing 10 $\mu$m in-situ spatial resolution. The results show a fill factor-normalized detection efficiency of 75% and a time resolution of about 130 ps across pixels. These findings represent a significant advancement toward developing high-efficiency SMSPD charged particle tracking systems with simultaneous precision timing, with potential applications in future accelerator-based experiments such as the FCC-ee and Muon Collider.

physics.ins-det↗

arXiv2025

Magnetic-Field and Temperature Limits of a Kinetic-Inductance Traveling-Wave Parametric Amplifier

Kinetic-inductance traveling-wave parametric amplifiers (KI-TWPAs) offer broadband near-quantum-limited amplification with high saturation power. Due to the high critical magnetic fields of high-kinetic-inductance materials, KI-TWPAs should be resilient to magnetic fields. In this work, we study how magnetic field and temperature affect the performance of a KI-TWPA based on a thin-NbTiN inverse microstrip with a Nb ground plane. This KI-TWPA can provide substantial signal-to-noise ratio improvement ($\Delta SNR$) up to in-plane magnetic fields of 0.35T and out-of-plane fields of 50mT, considerably higher than what has been demonstrated with TWPAs based on Josephson junctions. The field compatibility can be further improved by incorporating vortex traps and by using materials with higher critical fields. We also find that the gain does not degrade when the temperature is raised to 3K (limited by the Nb ground plane) while $\Delta SNR$ decreases with temperature consistently with expectation. This demonstrates that KI-TWPAs can be used in experiments that need to be performed at relatively high temperatures. The operability of KI-TWPAs in high magnetic field opens the door to a wide range of applications in spin qubits, spin ensembles, topological qubits, low-power NMR, and the search for axion dark matter.

quant-ph↗

arXiv2025

Microscopic Theory of Squeezed Light in Quantum Dot Systems

We present a cavity-QED theory for generating squeezed light from semiconductor quantum dots (QDs) integrated in microcavities. We formulate equations of motion for an inhomogeneously broadened QD ensemble that is incoherently pumped and simultaneously driven by a coherent seed field, solve for steady states, and compute the output-field quadrature variances. The analysis identifies operating conditions that yield amplitude-quadrature squeezing, with photon-number fluctuations reduced below the coherent-state limit and squeezing levels as large as 5 dB attainable with presently accessible QD and cavity parameters using only ~ 1 uW pump power. We further show that quantum correlations originating from four-wave mixing play a dual role: they both shape the gain spectrum and generate squeezing. These correlations constitute the quantum counterpart of the mean-field (semiclassical) mechanisms responsible for self-mode-locking in QD lasers and the ultra-narrow lasing linewidths achieved under self-injection locking.

quant-ph↗

arXiv2025

Temperature-Dependent Characterization of Large-Area Superconducting Microwire Array with Single-Photon Sensitivity in the Near-Infrared

Superconducting nanowire single photon detectors (SNSPDs) are a leading detector technology for time-resolved single-photon counting from the ultraviolet to the near-infrared regime. The recent advancement in single-photon sensitivity in micrometer-scale superconducting wires opens up promising opportunities to develop large area SNSPDs with applications in low background dark matter detection experiments. We present the first detailed temperature-dependent study of a 4-channel $1\times1$ mm$^{2}$ WSi superconducting microwire single photon detector (SMSPD) array, including the internal detection efficiency, dark count rate, and importantly the coincident dark counts across pixels. The detector shows saturated internal detection efficiency for photon wavelengths ranging from 635 nm to 1650 nm, time jitter of about 160 ps for 1060 nm photons, and a low dark count rate of about $10^{-2}$ Hz. Additionally, the coincidences of dark count rate across pixels are studied for the first time in detail, where we observed an excess of correlated dark counts, which has important implications for low background dark matter experiments. The results presented is the first step towards characterizing and developing SMSPD array systems and associated background for low background dark matter detection experiments.

physics.ins-det↗

arXiv2024

High Energy Particle Detection with Large Area Superconducting Microwire Array

We present the first detailed study of an 8-channel $2\times2$ mm$^{2}$ WSi superconducting microwire single photon detector (SMSPD) array exposed to 120 GeV proton beam and 8 GeV electron and pion beam at the Fermilab Test Beam Facility. The SMSPD detection efficiency was measured for the first time for protons, electrons, and pions, enabled by the use of a silicon tracking telescope that provided precise spatial resolution of 30 $\mu$m for 120 GeV protons and 130 $\mu$m for 8 GeV electrons and pions. The result demonstrated consistent detection efficiency across pixels and at different bias currents. Time resolution of 1.15 ns was measured for the first time for SMSPD with proton, electron, and pions, enabled by the use of an MCP-PMT which provided a ps-level reference time stamp. The results presented is the first step towards developing SMSPD array systems optimized for high energy particle detection and identification for future accelerator-based experiments.

hep-ex↗

arXiv2024

Frequency-domain multiplexing of SNSPDs with tunable superconducting resonators

This work culminates in a demonstration of an alternative Frequency Domain Multiplexing (FDM) scheme for Superconducting Nanowire Single-Photon Detectors (SNSPDs) using the Kinetic inductance Parametric UP-converter (KPUP) made out of NbTiN. There are multiple multiplexing architectures for SNSPDs that are already in use, but FDM could prove superior in applications where the operational bias currents are very low, especially for mid- and far-infrared SNSPDs. Previous FDM schemes integrated the SNSPD within the resonator, while in this work we use an external resonator, which gives more flexibility to optimize the SNSPD architecture. The KPUP is a DC-biased superconducting resonator in which a nanowire is used as its inductive element to enable sensitivity to current perturbations. When coupled to an SNSPD, the KPUP can be used to read out current pulses on the few $\mu$A scale. The KPUP is made out of NbTiN, which has high non-linear kinetic inductance for increased sensitivity at higher current bias and high operating temperature. Meanwhile, the SNSPD is made from WSi, which is a popular material for broadband SNSPDs. To read out the KPUP and SNSPD array, a software-defined radio platform and a graphics processing unit are used. Frequency Domain Multiplexed SNSPDs have applications in astronomy, remote sensing, exoplanet science, dark matter detection, and quantum sensing.

physics.ins-det↗

arXiv2024

Exploitation Strategies in Conditional Markov Chain Search: A case study on the three-index assignment problem

The Conditional Markov Chain Search (CMCS) is a framework for automated design of metaheuristics for discrete combinatorial optimisation problems. Given a set of algorithmic components such as hill climbers and mutations, CMCS decides in which order to apply those components. The decisions are dictated by the CMCS configuration that can be learnt offline. CMCS does not have an acceptance criterion; any moves are accepted by the framework. As a result, it is particularly good in exploration but is not as good at exploitation. In this study, we explore several extensions of the framework to improve its exploitation abilities. To perform a computational study, we applied the framework to the three-index assignment problem. The results of our experiments showed that a two-stage CMCS is indeed superior to a single-stage CMCS.

cs.AI↗

arXiv2022

Multiclass ASMA vs Targeted PGD Attack in Image Segmentation

Deep learning networks have demonstrated high performance in a large variety of applications, such as image classification, speech recognition, and natural language processing. However, there exists a major vulnerability exploited by the use of adversarial attacks. An adversarial attack imputes images by altering the input image very slightly, making it nearly undetectable to the naked eye, but results in a very different classification by the network. This paper explores the projected gradient descent (PGD) attack and the Adaptive Mask Segmentation Attack (ASMA) on the image segmentation DeepLabV3 model using two types of architectures: MobileNetV3 and ResNet50, It was found that PGD was very consistent in changing the segmentation to be its target while the generalization of ASMA to a multiclass target was not as effective. The existence of such attack however puts all of image classification deep learning networks in danger of exploitation.

cs.CV↗

arXiv2022

Provably efficient variational generative modeling of quantum many-body systems via quantum-probabilistic information geometry

The dual tasks of quantum Hamiltonian learning and quantum Gibbs sampling are relevant to many important problems in physics and chemistry. In the low temperature regime, algorithms for these tasks often suffer from intractabilities, for example from poor sample- or time-complexity. With the aim of addressing such intractabilities, we introduce a generalization of quantum natural gradient descent to parameterized mixed states, as well as provide a robust first-order approximating algorithm, Quantum-Probabilistic Mirror Descent. We prove data sample efficiency for the dual tasks using tools from information geometry and quantum metrology, thus generalizing the seminal result of classical Fisher efficiency to a variational quantum algorithm for the first time. Our approaches extend previously sample-efficient techniques to allow for flexibility in model choice, including to spectrally-decomposed models like Quantum Hamiltonian-Based Models, which may circumvent intractable time complexities. Our first-order algorithm is derived using a novel quantum generalization of the classical mirror descent duality. Both results require a special choice of metric, namely, the Bogoliubov-Kubo-Mori metric. To test our proposed algorithms numerically, we compare their performance to existing baselines on the task of quantum Gibbs sampling for the transverse field Ising model. Finally, we propose an initialization strategy leveraging geometric locality for the modelling of sequences of states such as those arising from quantum-stochastic processes. We demonstrate its effectiveness empirically for both real and imaginary time evolution while defining a broader class of potential applications.

quant-ph↗

arXiv2021

What Would Jiminy Cricket Do? Towards Agents That Behave Morally

When making everyday decisions, people are guided by their conscience, an internal sense of right and wrong. By contrast, artificial agents are currently not endowed with a moral sense. As a consequence, they may learn to behave immorally when trained on environments that ignore moral concerns, such as violent video games. With the advent of generally capable agents that pretrain on many environments, it will become necessary to mitigate inherited biases from environments that teach immoral behavior. To facilitate the development of agents that avoid causing wanton harm, we introduce Jiminy Cricket, an environment suite of 25 text-based adventure games with thousands of diverse, morally salient scenarios. By annotating every possible game state, the Jiminy Cricket environments robustly evaluate whether agents can act morally while maximizing reward. Using models with commonsense moral knowledge, we create an elementary artificial conscience that assesses and guides agents. In extensive experiments, we find that the artificial conscience approach can steer agents towards moral behavior without sacrificing performance.

cs.LG↗

arXiv2021

Machine Learning for Continuous Quantum Error Correction on Superconducting Qubits

Continuous quantum error correction has been found to have certain advantages over discrete quantum error correction, such as a reduction in hardware resources and the elimination of error mechanisms introduced by having entangling gates and ancilla qubits. We propose a machine learning algorithm for continuous quantum error correction that is based on the use of a recurrent neural network to identify bit-flip errors from continuous noisy syndrome measurements. The algorithm is designed to operate on measurement signals deviating from the ideal behavior in which the mean value corresponds to a code syndrome value and the measurement has white noise. We analyze continuous measurements taken from a superconducting architecture using three transmon qubits to identify three significant practical examples of non-ideal behavior, namely auto-correlation at temporal short lags, transient syndrome dynamics after each bit-flip, and drift in the steady-state syndrome values over the course of many experiments. Based on these real-world imperfections, we generate synthetic measurement signals from which to train the recurrent neural network, and then test its proficiency when implementing active error correction, comparing this with a traditional double threshold scheme and a discrete Bayesian classifier. The results show that our machine learning protocol is able to outperform the double threshold protocol across all tests, achieving a final state fidelity comparable to the discrete Bayesian classifier.

quant-ph↗

arXiv2019

On the capacitive properties of individual microtubules and their meshworks

Microtubules are hollow cylindrical polymers composed of the highly negatively-charged (~23e), high dipole moment (1750 D) protein a,b-tubulin. While the roles of microtubules in chromosomal segregation, macromolecular transport and cell migration are relatively well-understood, studies on the electrical properties of microtubules have only recently gained strong interest. Here, we show that while microtubules at physiological concentrations increase solution capacitance, free tubulin has no appreciable effect. For a particular microtubule concentration, we were able to quantify these effects by determining the capacitance and resistance of a single 20 um-long microtubule to be 1.86 x 10^(-12) F and 1.07 x 10^12 Ohms respectively. Further, we observed a decrease in electrical resistance of solution, with charge transport peaking between 20-60 Hz in the presence of microtubules, consistent with recent findings that microtubules exhibit electric oscillations at such low frequencies. Our results show that in addition to macromolecular transport, microtubules also act as charge-storage devices through counterionic condensation across a broad frequency spectrum. We conclude with a hypothesis of an electrically-tunable cytoskeleton where the dielectric properties of tubulin are polymerization-state dependent.

physics.bio-ph↗

arXiv2018

Room Temperature Magnetic Order in Air-Stable Ultra-Thin Iron Oxide

Certain two-dimensional (2D) materials exhibit intriguing properties such as valley polarization, ferroelectricity, superconductivity and charge-density waves. Many of these materials can be manually assembled into atomic-scale multilayer devices under ambient conditions, owing to their exceptional chemical stability. Efforts have been made to add a magnetic degree of freedom to these 2D materials via defects, but only local magnetism has been achieved. Only with the recent discoveries of 2D materials supporting intrinsic ferromagnetism have stacked spintronic devices become realistic. Assembling 2D multilayer devices with these ferromagnets under ambient conditions remains challenging due to their sensitivity to environmental degradation, and magnetic order at room temperature is rare in van der Waals materials. Here, we report the growth of air-stable ultra-thin epsilon-phase iron oxide crystals that exhibit magnetic order at room temperature. These crystals require no passivation and can be prepared in large quantity by cost-effective chemical vapor deposition (CVD). We find that the epsilon phase, which is energetically unfavorable and does not form in bulk, can be easily made in 2D down to a seven unit-cell thickness. Magneto-optical Kerr effect (MOKE) magnetometry of individual crystals shows that even at this ultrathin limit the epsilon phase exhibits robust magnetism with coercive fields of hundreds of mT. These measurements highlight the advantages of ultrathin iron oxide as a promising candidate towards air-stable 2D magnetism and integration into 2D spintronic devices.

cond-mat.mtrl-sci↗

arXiv2014

Electrical detection of ferromagnetic resonance in ferromagnet/n-GaAs heterostructures by tunneling anisotropic magnetoresistance

We observe a dc voltage peak at ferromagnetic resonance (FMR) in samples consisting of a single ferromagnetic (FM) layer grown epitaxially on the $\mathit{n-}$GaAs (001) surface. The FMR peak is detected as an interfacial voltage with a symmetric line shape and is present in samples based on various FM/$n$-GaAs hetrostructures, including Co$_{2}$MnSi/$n$-GaAs, Co$_{2}$FeSi/$n$-GaAs and Fe/$n$-GaAs. We show that the interface bias voltage dependence of the FMR signal is identical to that of the tunneling anisotropic magnetoresistance (TAMR) over most of the bias range. Furthermore, we show how the precessing magnetization yields a dc FMR signal through the TAMR effect and how the TAMR phenomenon can be used to predict the angular dependence of the FMR signal. This TAMR-induced FMR peak can be observed under conditions where no spin accumulation is present and no spin-polarized current flows in the semiconductor.

cond-mat.mtrl-sci↗