arXiv subjects

Yonatan Cohen

Publications and source records attributed to Yonatan Cohen.

13 recordsLinked to original sources

arXiv2025

Impacts of Decoder Latency on a Utility-Scale Quantum Computer Architecture

The speed of a fault-tolerant quantum computer depends in large part on the reaction time of its classical electronics, that is, the total time required by decoders and controllers to determine the outcome of a logical measurement and execute subsequent conditional logical operations. Despite its importance, the reaction time and its impact on the design of a logical microarchitecture of a quantum computer are not well understood. In this work, we perform a detailed system-level analysis of the classical and quantum resource requirements of a surface code based architecture. To this end, we construct a model of the reaction time in which the decoder latency is based on parallel space- and time-window decoding methods. In addition, we draw communication latencies from our envisioned quantum execution environment, which comprises a high-speed network of quantum processing units, controllers, decoders, and high-performance computing nodes. We use this model to estimate the increase in the logical error rate of magic state injections as a function of the reaction time. We then show how the microarchitecture can be optimized with respect to the reaction time, and present full-system quantum resource estimates based on realistic hardware noise parameters for executing utility-scale quantum circuits of the Fermi-Hubbard model (2562 logical qubits and $4$$\times$$10^6$ $T$ gates) and NMR spectral prediction (241 logical qubits and $5.11$$\times$$10^{11}$ $T$ gates). We numerically determine the impact of improving reaction time on the code distance required for the core processor and on the size of the resource state factory. Moreover, we analyze how decoder speeds constrain the size of practically executable circuits, and show that state-of-the-art decoders will require a performance improvement of at least an order of magnitude to execute utility-scale quantum algorithms within days.

quant-ph↗

arXiv2024

Controller-decoder system requirements derived by implementing Shor's algorithm with surface code

Quantum Error Correction (QEC) is regarded as the most promising path to quantum advantage. The success of QEC relies on achieving quantum gate fidelities below the error threshold of the QEC code, while accurately decoding errors through classical processing of the QEC stabilizer measurements. In this paper, we uncover the critical system-level requirements from a controller-decoder system (CDS) necessary to successfully execute the next milestone in QEC: a non-Clifford circuit. Using a representative non-Clifford circuit, of Shor factorization algorithm for the number 21, we convert the logical-level circuit to a QEC surface code circuit and finally to the physical level circuit. By taking into account realistic implementation aspects using typical superconducting qubit processor parameters, we reveal a broad range of core requirements from any CDS aimed at performing error corrected quantum computation. Our findings indicate that the controller-decoder closed-loop latency must remain within tens of microseconds, achievable by distributing decoding data into several decoders while ensuring fast communication between decoders and with the controller. By extending existing simulation techniques, we simulate the complete fault-tolerant factorization circuit at the physical level, demonstrating that near-term hardware performance in the scale of 0.1% physical error rates and 1000 qubits, are sufficient for a successful circuit execution. Overall, the requirements outlined here set the stage for near- and medium-term experimental realizations of non-Clifford QEC circuits.

quant-ph↗

arXiv2024

How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits

In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits. Nevertheless, there are significant outstanding challenges in quantum hardware, fabrication, software architecture, and algorithms on the path towards a full-stack scalable quantum computing technology. Here, we provide a comprehensive review of these scaling challenges. We show how to facilitate scaling by adopting existing semiconductor technology to build much higher-quality qubits, employing systems engineering approaches, and performing distributed heterogeneous quantum-classical computing. We provide a detailed resource and sensitivity analysis for quantum applications on surface-code error-corrected quantum computers given current, target, and desired hardware specifications based on superconducting qubits, accounting for a realistic distribution of errors. We provide comprehensive resource estimates for several utility-scale applications including quantum chemistry calculations, catalyst design, NMR spectroscopy, and Fermi-Hubbard simulation. We show that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration. Furthermore, we introduce high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical optimization, machine learning, and quantum simulation tasks in a cost-effective manner.

quant-ph↗

arXiv2024

Preparing Schr\"odinger cat states in a microwave cavity using a neural network

Scaling up quantum computing devices requires solving ever more complex quantum control tasks. Machine learning has been proposed as a promising approach to tackle the resulting challenges. However, experimental implementations are still scarce. In this work, we demonstrate experimentally a neural-network-based preparation of Schr\"odinger cat states in a cavity coupled dispersively to a qubit. We show that it is possible to teach a neural network to output optimized control pulses for a whole family of quantum states. After being trained in simulations, the network takes a description of the target quantum state as input and rapidly produces the pulse shape for the experiment, without any need for time-consuming additional optimization or retraining for different states. Our experimental results demonstrate more generally how deep neural networks and transfer learning can produce efficient simultaneous solutions to a range of quantum control tasks, which will benefit not only state preparation but also parametrized quantum gates.

quant-ph↗

arXiv2024

Two-level system hyperpolarization using a quantum Szilard engine

The innate complexity of solid state physics exposes superconducting quantum circuits to interactions with uncontrolled degrees of freedom degrading their coherence. By using a simple stabilization sequence we show that a superconducting fluxonium qubit is coupled to a two-level system (TLS) environment of unknown origin, with a relatively long energy relaxation time exceeding $50\,\text{ms}$. Implementing a quantum Szilard engine with an active feedback control loop allows us to decide whether the qubit heats or cools its TLS environment. The TLSs can be cooled down resulting in a four times lower qubit population, or they can be heated to manifest themselves as a negative temperature environment corresponding to a qubit population of $\sim 80\,\%$. We show that the TLSs and the qubit are each other's dominant loss mechanism and that the qubit relaxation is independent of the TLS populations. Understanding and mitigating TLS environments is therefore not only crucial to improve qubit lifetimes but also to avoid non-Markovian qubit dynamics.

quant-ph↗

arXiv2023

Quantum-classical processing and benchmarking at the pulse-level

Towards the practical use of quantum computers in the NISQ era, as well as the realization of fault-tolerant quantum computers that utilize quantum error correction codes, pressing needs have emerged for the control hardware and software platforms. In particular, a clear demand has arisen for platforms that allow classical processing to be integrated with quantum processing. While recent works discuss the requirements for such quantum-classical processing integration that is formulated at the gate-level, pulse-level discussions are lacking and are critically important. Moreover, defining concrete performance benchmarks for the control system at the pulse-level is key to the necessary quantum-classical integration. In this work, we categorize the requirements for quantum-classical processing at the pulse-level, demonstrate these requirements with a variety of use cases, including recently published works, and propose well-defined performance benchmarks for quantum control systems. We utilize a comprehensive pulse-level language that allows embedding universal classical processing in the quantum program and hence allows for a general formulation of benchmarks. We expect the metrics defined in this work to form a solid basis to continue to push the boundaries of quantum computing via control systems, bridging the gap between low-level and application-level implementations with relevant metrics.

quant-ph↗

arXiv2023

Benchmarking the ability of a controller to execute quantum error corrected non-Clifford circuits

Reaching fault-tolerant quantum computation relies on the successful implementation of non-Clifford circuits with quantum error correction (QEC). In QEC, quantum gates and measurements encode quantum information into an error-protected Hilbert space, while classical processing decodes the measurements into logical errors. QEC non-Clifford gates pose the greatest computation challenge from the classical controller perspective, as they require mid-circuit decoding-dependent feed-forward, modifying the physical gate sequence based on the decoding outcome of previous measurements within the same circuit. In this work, we introduce the first benchmarks to holistically evaluate the capability of a combined controller-decoder system to run non-Clifford QEC circuits. We show that executing an error-corrected non-Clifford circuit, comprised of numerous non-Clifford gates, strictly hinges upon the classical controller-decoder system. Particularly, its ability to perform decoding-based feed-forward with low-latency, defined as the time between the last measurement required for decoding and the dependent mid-circuit quantum operation. We analyze how the system latency dictates the circuit operational regime: latency divergence, classical-controller-limited runtime, or quantum-operation-limited runtime. Based on this understanding, we introduce latency-based benchmarks to set a standard for developing QEC control systems as an essential components of fault-tolerant quantum computation.

quant-ph↗

arXiv2023

Real-time frequency estimation of a qubit without single-shot-readout

Quantum sensors can potentially achieve the Heisenberg limit of sensitivity over a large dynamic range using quantum algorithms. The adaptive phase estimation algorithm (PEA) is one example that was proven to achieve such high sensitivities with single-shot readout (SSR) sensors. However, using the adaptive PEA on a non-SSR sensor is not trivial due to the low contrast nature of the measurement. The standard approach to account for the averaged nature of the measurement in this PEA algorithm is to use a method based on `majority voting'. Although it is easy to implement, this method is more prone to mistakes due to noise in the measurement. To reduce these mistakes, a binomial distribution technique from a batch selection was recently shown theoretically to be superior, as all ranges of outcomes from an averaged measurement are considered. Here we apply, for the first time, real-time non-adaptive PEA on a non-SSR sensor with the binomial distribution approach. We compare the mean square error of the binomial distribution method to the majority-voting approach using the nitrogen-vacancy center in diamond at ambient conditions as a non-SSR sensor. Our results suggest that the binomial distribution approach achieves better accuracy with the same sensing times. To further shorten the sensing time, we propose an adaptive algorithm that controls the readout phase and, therefore, the measurement basis set. We show by numerical simulation that adding the adaptive protocol can further improve the accuracy in a future real-time experiment.

quant-ph↗

arXiv2019

Synthesizing a Fractional v=2/3 State from Particle and Hole States

Topological edge-reconstruction occurs in hole-conjugate states of the fractional quantum Hall effect. The frequently studied polarized state of filling factor v=2/3 was originally proposed to harbor two counter-propagating edge modes: a downstream v=1 and an upstream v=1/3. However, charge equilibration between these two modes always led to an observed downstream v=2/3 charge mode accompanied by an upstream neutral mode (preventing an observation of the original proposal). Here, we present a new approach to synthetize the v=2/3 edge mode from its basic counter-propagating charged constituents, allowing a controlled equilibration between the two counter-propagating charge modes. This novel platform is based on a carefully designed double-quantum-well, which hosts two populated electronic sub-bands (lower and upper), with corresponding filling factors, vl & vu. By separating the 2D plane to two gated intersecting halves, each with different fillings, counter-propagating chiral modes can be formed along the intersection line. Equilibration between these modes can be controlled with the top gates' voltage and the magnetic field. Our measurements of the two-terminal conductance G2T and the presence of a neutral mode allowed following the transition from the non-equilibrated charged modes, manifested by G2T=(4/3)e2/h, to the fully equilibrated modes, with a downstream charge mode with G2T=(2/3)e2/h accompanied by an upstream neutral mode.

cond-mat.mes-hall↗

arXiv2017

Robust integer and fractional helical modes in the quantum Hall effect

Electronic systems harboring one dimensional helical modes, where the spin and momentum of the electron are locked, have lately become an important field of its own. When coupled to a conventional superconductor, such systems are expected to manifest topological superconductivity, a unique phase that gives rise to exotic Majorana zero modes. Even more interesting are fractional helical states which have not been observed before and which open the route for the realization of the generalized para fermions quasiparticles. Possessing non abelian exchange statistics, these quasiparticles may serve as building blocks in topological quantum computing. Here, we present a new approach to form protected one dimensional helical and fractional helical edge modes in the quantum Hall regime. The novel platform is based on a carefully designed double quantum well structure in a high mobility GaAs based system. In turn, the quantum well hosts two sub bands of 2D electrons, each tuned to the quantum Hall effect regime. By electrostatic gating of different areas of the structure, counter propagating integer, as well as fractional, edge modes, belonging to Landau levels with opposite spins are formed, rendering the modes helical. We demonstrate that due to spin protection, these helical modes remain ballistic, without observed mixing for large distances. In addition to the formation of helical modes, this new platform can be exploited as a rich playground for an artificial induction of compounded fractional edge modes, as well as construction of interferometers based on chiral edge modes.

cond-mat.mes-hall↗

arXiv2017

Non-local Supercurrent of Quartets in a Three-Terminal Josephson Junction

We report an observation of a new, non dissipative and non local supercurrent, carried by quartets; each consisting of four entangled electrons. The supercurrent is a result of a novel Andreev bound state (ABS), formed among three superconducting terminals. While in a two-terminal Josephson junction the usual ABS, and thus the DC Josephson current, exist only in equilibrium, in the present realization the ABS exists also in the strongly nonlinear regime (biased terminals). The presence of supercurrent carried by quartets was established by performing non-local conductance and cross-correlation of current fluctuations measurements, in different devices made of aluminum-InAs nanowire junctions. An extensive and detailed theoretical study is intertwined with the experimental results.

cond-mat.mes-hall↗

arXiv2016

MBE growth of self-assisted InAs nanowires on graphene

Self-assisted growth of InAs nanowires on graphene by molecular beam epitaxy is reported. Nanowires with diameter of ~50 nm and aspect ratio of up to 100 were achieved. The morphological and structural properties of the nanowires were carefully studied by changing the substrate from bilayer graphene through buffer layer to quasi-free-standing monolayer graphene. The positional relation of the InAs NWs with the graphene substrate was determined. A 30° orientation configuration of some of the InAs NWs is shown to be related to the surface corrugation of the graphene substrate. InAs NW-based devices for transport measurements were fabricated, and the conductance measurements showed a semi-ballistic behavior. In Josephson junction measurements in the non-linear regime, Multiple Andreev Reflections were observed, and an inelastic scattering length of about 900 nm was derived.

cond-mat.mtrl-sci↗

arXiv2016

Charge of a quasiparticle in a superconductor

Non-linear charge transport in SIS Josephson junctions has a unique signature in the shuttled charge quantum between the two superconductors. In the zero-bias limit Cooper pairs, each with twice the electron charge, carry the Josephson current. An applied bias $V_{SD}$ leads to multiple Andreev reflections (MAR), which in the limit of weak tunneling probability should lead to integer multiples of the electron charge $ne$ traversing the junction, with $n$ integer larger than $2Δ/eV_{SD}$ and $Δ$ the superconducting order parameter. Exceptionally, just above the gap, $eV_{SD}>2Δ$, with Andreev reflections suppressed, one would expect the current to be carried by partitioned quasiparticles; each with energy dependent charge, being a superposition of an electron and a hole. Employing shot noise measurements in an SIS junction induced in an InAs nanowire (with noise proportional to the partitioned charge), we first observed quantization of the partitioned charge $q=e^*/e=n$, with $n=1-4$; thus reaffirming the validity of our charge interpretation. Concentrating next on the bias region $eV_{SD}{\approx}2Δ$, we found a reproducible and clear dip in the extracted charge to $q{\approx}0.6$, which, after excluding other possibilities, we attribute to the partitioned quasiparticle charge. Such dip is supported by numerical simulations of our SIS structure.

cond-mat.mes-hall↗