Near-term quantum algorithms for linear systems of equations with regression loss functions

Solving linear systems of equations is essential for many problems in science and technology, including problems in machine learning. Existing quantum algorithms have demonstrated the potential for large speedups, but the required quantum resources are not immediately available on near-term quantum devices. In this work, we study near-term quantum algorithms for linear systems of equations, with a focus on the two-norm and Tikhonov regression settings. We investigate the use of variational algorithms and analyze their optimization landscapes. There exist types of linear systems for which variational algorithms designed to avoid barren plateaus, such as properly-initialized imaginary time evolution and adiabatic-inspired optimization, suffer from a different plateau problem. To circumvent this issue, we design near-term algorithms based on a core idea: the classical combination of variational quantum states (CQS). We exhibit several provable guarantees for these algorithms, supported by the representation of the linear system on a so-called ansatz tree. The CQS approach and the ansatz tree also admit the systematic application of heuristic approaches, including a gradient-based search. We have conducted numerical experiments solving linear systems as large as 2300 × 2300 by considering cases where we can simulate the quantum algorithm efficiently on a classical computer. Our methods may provide benefits for solving linear systems within the reach of near-term quantum devices.

Application of Raman spectroscopy for understanding the mineralogical composition of ancient copper slags (Timna, Israel)

<p>Prehistoric slags (Late Bronze Age to early Iron Age, ca. 1300 – 1000 BC) from copper metallurgy were sampled at the archaeological site no.2 in Timna, Israel. A classical combination of analytical methods for this kind of samples (optical and scanning electron microscopy, X-ray diffraction analysis, and electron microprobe analysis) was complemented with Raman microspectroscopy.</p><p>Raman microspectroscopy is a strong tool for phase or mineral identification in general, and when coupled with the methods for determination of the chemical composition such as electron probe microanalysis, it provides a comprehensive phase description of the sample. Slags are generally composed of both crystalline and amorphous glass-like phases and include metals, intermetallic compounds and alloys, sulfides, oxides, silicates, silicate glasses and carbonaceous fuel residues. With the exception of pure metals and their respective alloys, all these phases can be theoretically analyzed using Raman microspectroscopy. However, laser-induced fluorescence can become a major issue, owing to a presence of many different metallic elements. Selection of appropriate laser excitation wavelength can reduce the amount of fluorescence. Using Raman microspectroscopy it was possible to identify major silicate phases such as olivine (fayalite) and clinopyroxene (hedenbergite). Using this technique the crystallinity of iron oxides was identified and magnetite and hematite were differentiated. Despite the fact that Cu sulphides have simple Raman spectra with only few diagnostic bands, digenite and chalcopyrite were confirmed in the Timna slags. This study was supported by the Czech Science Foundation project (GAČR 19-18513S). The sampling campaign was carried out in the framework of Erasmus+ Mobility exchange programme between Charles University, Prague, Czech Republic (CUNI) and Hebrew University in Jerusalem, Israel (HUJI).   </p>

STAT3 Relays a Differential Response to Melanoma-Associated NRAS Mutations

Melanoma patients carrying an oncogenic NRAS mutation represent 20% of all cases and present worse survival, relapse rate and therapy response than patients with wild type NRAS or with BRAF mutations. Nevertheless, no efficient targeted therapy has emerged so far for this group of patients in comparison with the classical combination of BRAF and MEK inhibitors for the patient group carrying a BRAF mutation. NRAS key downstream actors should therefore be identified for drug targeting, possibly in combination with MEK inhibitors. Here, we investigated the influence of different melanoma-associated NRAS mutations (codon 12, 13 or 61) on several parameters such as oncogene-induced senescence, cell proliferation, migration or colony formation in immortalized melanocytes and in melanoma cell lines. We identified AXL/STAT3 axis as a main regulator of NRASQ61–induced oncogene-induced senescence (OIS) and observed that NRASQ61 mutations are not only more tumorigenic than NRASG12/13 mutations but also associated to STAT3 activation. In conclusion, these data bring new evidence of the potential tumorigenic role of STAT3 in NRAS-mutant melanomas and will help improving current therapy strategies for this particular patient group.

Marked synergism of cytotoxic agents with either a prenylation inhibitor or M-TOR inhibitor in acute leukemia cell lines: Potential clinical implications

13103 Background: The most combinations of anticancer drugs are based upon empiricism. The potential permutations of drugs overwhelm the clinical trials system. Acute leukemia is sensitive to a variety of agents but relapses are common. Targeted agents are attractive new venues of therapy both as single agents and in combination with older agents. Isobologram median effect analysis allows up to three agents to be studied together in vitro to identify interesting combinations. We evaluated a commercially available statin, fluvastatin, to block prenylation which affects a variety of pathways, rapamycin and its experimental analogue RAD001 as M-TOR inhibitors to block downstream of the AKT pathway, and cytotoxic agents. Methods: The human leukemia cell lines AML-193 and KG-1 were obtained from ATTC (Rockville, MD), fluvastatin and RAD001 from Novartis Pharma, and the other agents from Sigma-Aldrich (St. Louis, MO). The IC50 of the single agent was determined by a 72 hr incubation of log growth cells using a MTT assay and the EZ-ED50 program (Perrella Scientific, Conyers, CA). The dosages of all agents were at clinically achievable concentrations. All reported values were the means of at least 3 experiments with each study using 4 wells per point. For isobologram analysis, a minimum of 8 concentrations of drug mixtures were studied above and below the IC50. Median effect CI values less than 1 are synergistic. Results: Doublets of fluvastatin with Ara-C (0.7), daunomycin (0.4), idarubicin (0.7), RAD001 (0.5), or rapamycin (0.3) demonstrated synergy. Doublets of RAD001 with Ara-C (0.3), daunomycin (0.7), or idarubicin (0.5) demonstrated synergy. Triplets of RAD001/daunorubicin/Ara-C, RAD001/daunomycin/fluvastatin, and RAD001/Ara-C/idarubicin all demonstrated marked synergy in both cell lines. Conclusion: A new potential non classical combination for further investigation is RAD001 or rapamycin with an inhibitor of prenylation such as fluvastatin. Additional potential combinations include cytotoxics with either fluvastatin or RAD001, and triplet combinations. No significant financial relationships to disclose.