Searcharxiv⌕ Search

arXiv subjects

Yossi Weinstein

Publications and source records attributed to Yossi Weinstein.

14 recordsLinked to original sources
arXiv2026

Benchmarking Quantum Computers via Protocols, Comparing Superconducting and Ion-Trap Quantum Technology

Both Superconducting and Ion-Trap are leading quantum architectures common in the current landscape of the quantum computing field, each with distinct characteristics and operational constraints. Understanding and measuring the underlying \underline{quantumness} of these devices is essential for assessing their readiness for practical applications and guiding future progress and research. Building on earlier work (Meirom, Mor and Weinstein Arxiv 2505.12441), we utilize a benchmarking strategy applicable for comparing these two architectures by measuring "quantumness" directly on optimal sub-chips. Distinct from existing metrics, our approach employs rigorous binary fidelity thresholds derived from the classical limits of state transfer. This enables us to definitively establish quantum advantage of a designated sub-region. Here we apply this quality assurance methodology to platforms from both technologies. This comparison provides a protocol-based evaluation of quantumness advantage, revealing not only the strengths and weaknesses of each tested chip and its sub-chips but also offering a common language for their assessment. By abstracting away technical differences in the final result, we demonstrate a benchmarking strategy that bridges the gap between disparate quantum-circuit technologies, enabling fair performance comparisons and establishing a critical foundation for evaluating future claims of quantum advantage. This work was made possible by policies of two companies who enable independent and objective assessment on their quantum computers and sub-chips. In the name of science, we encourage other companies to emulate the independent qubit availability and the fair pricing which allow researchers to preform such assessments.

quant-ph↗
arXiv2026

Benchmarking Quantum Computers via Protocols, Comparing IBM's Heron vs IBM's Eagle

As quantum computing hardware rapidly advances, objectively evaluating the capabilities and error rates of new processors remains a critical challenge for the field. A clear and realistic understanding of current quantum performance is essential for guiding research priorities and driving meaningful progress. In this work, we apply and extend a protocol-based benchmarking methodology (Meirom, Mor, Weinstein Arxiv 2505.12441) that utilizes well-defined \underline{quantumness} thresholds. By evaluating performance at protocol level rather than the gate level, this approach provides a transparent and intuitive assessment of whether specific quantum processors, or isolated sub-chips within them, can demonstrate a practical quantum advantage. To illustrate the utility of this method, we compare two generations of IBM quantum computers: the older Eagle architecture and the newer Heron architecture. Our findings reveal the genuine operational strengths and limitations of these devices, demonstrating substantial performance improvements in the newer Heron generation. This work was made possible by IBM Quantum policies that enable independent and objective assessment of its quantum computers and sub-chips. We strongly encourage other companies to emulate the independent qubit availability and the fair pricing that allow researchers to perform such assessments.

quant-ph↗
arXiv2025

Benchmarking quantum computers via protocols

Benchmarking quantum computers often deals with the parameters of single qubits or gates and sometimes deals with algorithms run on an entire chip or a noisy simulator of a chip. Here we propose the idea of using protocols to benchmark quantum computers. The advantage of using protocols, especially the seven suggested here, over other benchmarking methods is that there is a clear cutoff (i.e., a threshold) distinguishing quantumness from classicality for each of our protocols. The protocols we suggest enable a comparison among various circuit-based quantum computers, and also between real chips and their noisy simulators. This latter method may then be used to better understand the various types of noise of the real chips. We use some of these protocols to answer an important question: ``How many effective qubits are there in this N-qubit quantum computer/simulator?'', and we then conclude which effective sub-chips can be named ``truly-quantum''.

quant-ph↗
arXiv2017

Heat-Bath Algorithmic Cooling with correlated qubit-environment interactions

Controlled preparation of highly pure quantum states is at the core of practical applications of quantum information science, from the state initialization of most quantum algorithms to a reliable supply of ancilla qubits that satisfy the fault-tolerance threshold for quantum error correction. Heat-bath algorithmic cooling has been shown to purify qubits by controlled redistribution of entropy and multiple contact with a bath, not only for ensemble implementations but also for technologies with strong but imperfect measurements. However, an implicit restriction about the interaction with the bath has been assumed in previous work. In this paper, we show that better purification can be achieved by removing that restriction. More concretely, we include correlations between the system and the bath, and we take advantage of these correlations to pump entropy out of the system into the bath. We introduce a tool for cooling algorithms, which we call "state-reset", obtained when the coupling to the environment is generalized from individual-qubits relaxation to correlated-qubit relaxation. We present improved cooling algorithms which lead to an increase of purity beyond all the previous work, and relate our results to the Nuclear Overhauser Effect.

quant-ph↗
arXiv2015

Algorithmic Cooling in Liquid State NMR

Algorithmic cooling is a method that employs thermalization to increase qubit purification level, namely it reduces the qubit-system's entropy. We utilized gradient ascent pulse engineering (GRAPE), an optimal control algorithm, to implement algorithmic cooling in liquid state nuclear magnetic resonance. Various cooling algorithms were applied onto the three qubits of $^{13}$C$_2$-trichloroethylene, cooling the system beyond Shannon's entropy bound in several different ways. In particular, in one experiment a carbon qubit was cooled by a factor of 4.61. This work is a step towards potentially integrating tools of NMR quantum computing into in vivo magnetic resonance spectroscopy.

quant-ph↗
arXiv2014

Experimental Heat-Bath Cooling of Spins

Algorithmic cooling (AC) is a method to purify quantum systems, such as ensembles of nuclear spins, or cold atoms in an optical lattice. When applied to spins, AC produces ensembles of highly polarized spins, which enhance the signal strength in nuclear magnetic resonance (NMR). According to this cooling approach, spin-half nuclei in a constant magnetic field are considered as bits, or more precisely, quantum bits, in a known probability distribution. Algorithmic steps on these bits are then translated into specially designed NMR pulse sequences using common NMR quantum computation tools. The $algorithmic$ cooling of spins is achieved by alternately combining reversible, entropy-preserving manipulations (borrowed from data compression algorithms) with $selective$ $reset$, the transfer of entropy from selected spins to the environment. In theory, applying algorithmic cooling to sufficiently large spin systems may produce polarizations far beyond the limits due to conservation of Shannon entropy. Here, only selective reset steps are performed, hence we prefer to call this process "heat-bath" cooling, rather than algorithmic cooling. We experimentally implement here two consecutive steps of selective reset that transfer entropy from two selected spins to the environment. We performed such cooling experiments with commercially-available labeled molecules, on standard liquid-state NMR spectrometers. Our experiments yielded polarizations that $bypass$ $Shannon's$ $entropy$-$conservation$ $bound$, so that the entire spin-system was cooled. This paper was initially submitted in 2005, first to Science and then to PNAS, and includes additional results from subsequent years (e.g. for resubmission in 2007). The Postscriptum includes more details.

quant-ph↗
arXiv2014

Prospects and Limitations of Algorithmic Cooling

Heat-bath algorithmic cooling (AC) of spins is a theoretically powerful effective cooling approach, that (ideally) cools spins with low polarization exponentially better than cooling by reversible entropy manipulations alone. Here, we investigate the limitations and prospects of AC. For non-ideal and semioptimal AC, we study the impact of finite relaxation times of reset and computation spins on the achievable effective cooling. We derive, via simulations, the attainable cooling levels for given ratios of relaxation times using two semioptimal practicable algorithms. We expect this analysis to be valuable for the planning of future experiments. For ideal and optimal AC, we make use of lower bounds on the number of required reset steps, based on entropy considerations, to present important consequences of using AC as a tool for improving signal-to-noise ratio in liquid-state magnetic resonance spectroscopy. We discuss the potential use of AC for noninvasive clinical diagnosis and drug monitoring, where it may have significantly lower specific absorption rate (SAR) with respect to currently used methods.

quant-ph↗
arXiv2013

Quantum Computing Gates via Optimal Control

We demonstrate the use of optimal control to design two entropy-manipulating quantum gates which are more complex than the corresponding, commonly used, gates, such as CNOT and Toffoli (CCNOT): A 2-qubit gate called PE (polarization exchange) and a 3-qubit gate called COMP (polarization compression) were designed using GRAPE, an optimal control algorithm. Both gates were designed for a three-spin system. Our design provided efficient and robust NMR radio frequency (RF) pulses for 13C2-trichloroethylene (TCE), our chosen three-spin system. We then experimentally applied these two quantum gates onto TCE at the NMR lab. Such design of these gates and others could be relevant for near-future applications of quantum computing devices.

quant-ph↗
arXiv2011

Heat-Bath Cooling of Spins in Two Amino Acids

Heat-bath cooling is a component of practicable algorithmic cooling of spins, an approach which might be useful for in vivo 13C spectroscopy, in particular for prolonged metabolic processes where substrates that are hyperpolarized ex-vivo are not effective. We applied heat-bath cooling to 1,2-13C2-amino acids, using the alpha protons to shift entropy from selected carbons to the environment. For glutamate and glycine, both carbons were cooled by about 2.5-fold, and in other experiments the polarization of C1 nearly doubled while all other spins had equilibrium polarization, indicating reduction in total entropy. The effect of adding Magnevist, a gadolinium contrast agent, on heat-bath cooling of glutamate was investigated.

quant-ph↗
arXiv2011

Semi-optimal Practicable Algorithmic Cooling

Algorithmic Cooling (AC) of spins applies entropy manipulation algorithms in open spin-systems in order to cool spins far beyond Shannon's entropy bound. AC of nuclear spins was demonstrated experimentally, and may contribute to nuclear magnetic resonance (NMR) spectroscopy. Several cooling algorithms were suggested in recent years, including practicable algorithmic cooling (PAC) and exhaustive AC. Practicable algorithms have simple implementations, yet their level of cooling is far from optimal; Exhaustive algorithms, on the other hand, cool much better, and some even reach (asymptotically) an optimal level of cooling, but they are not practicable. We introduce here semi-optimal practicable AC (SOPAC), wherein few cycles (typically 2-6) are performed at each recursive level. Two classes of SOPAC algorithms are proposed and analyzed. Both attain cooling levels significantly better than PAC, and are much more efficient than the exhaustive algorithms. The new algorithms are shown to bridge the gap between PAC and exhaustive AC. In addition, we calculated the number of spins required by SOPAC in order to purify qubits for quantum computation. As few as 12 and 7 spins are required (in an ideal scenario) to yield a mildly pure spin (60% polarized) from initial polarizations of 1% and 10%, respectively. In the latter case, about five more spins are sufficient to produce a highly pure spin (99.99% polarized), which could be relevant for fault-tolerant quantum computing.

quant-ph↗
arXiv2007

Optimal Algorithmic Cooling of Spins

Algorithmic Cooling (AC) of Spins is potentially the first near-future application of quantum computing devices. Straightforward quantum algorithms combined with novel entropy manipulations can result in a method to improve the identification of molecules. We introduce here several new exhaustive cooling algorithms, such as the Tribonacci and k-bonacci algorithms. In particular, we present the ``all-bonacci'' algorithm, which appears to reach the maximal degree of cooling obtainable by the optimal AC approach.

quant-ph↗
arXiv2005

Experimental Heat-Bath Cooling of Spins

Algorithmic cooling is a novel technique to generate ensembles of highly polarized spins, which could significantly improve the signal strength in Nuclear Magnetic Resonance (NMR) spectroscopy. It combines reversible (entropy-preserving) manipulations and irreversible controlled interactions with the environment, using simple quantum computing techniques to increase spin polarization far beyond the Shannon entropy-conservation bound. Notably, thermalization is beneficially employed as an integral part of the cooling scheme, contrary to its ordinary destructive implications. We report the first cooling experiments bypassing Shannon's entropy-conservation bound, performed on a standard liquid-state NMR spectrometer. We believe that this experimental success could pave the way for the first near-future application of quantum computing devices.

quant-ph↗
arXiv2005

Paramagnetic Materials and Practical Algorithmic Cooling for NMR Quantum Computing

Algorithmic Cooling is a method that uses novel data compression techniques and simplecquantum computing devices to improve NMR spectroscopy, and to offer scalable NMR quantum computers. The algorithm recursively employs two steps. A reversible entropy compression of the computation quantum-bits (qubits) of the system and an irreversible heat transfer from the system to the environment through a set of reset qubits that reach thermal relaxation rapidly. Is it possible to experimentally demonstrate algorithmic cooling using existing technology? To allow experimental algorithmic cooling, the thermalization time of the reset qubits must be much shorter than the thermalization time of the computation qubits. However such thermalization-times ratios have yet to be reported. We investigate here the effect of a paramagnetic salt on the thermalization-times ratio of computation qubits (carbons) and a reset qubit (hydrogen). We show that the thermalization-times ratio is improved by approximately three-fold. Based on this result, an experimental demonstration of algorithmic cooling by thermalization and magnetic ions is currently performed by our group and collaborators.

quant-ph↗